X_ml
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y
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0
1
num_classes
int64
2
2
num_features
int64
9
9
num_idx
list
cat_idx
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cat_dim
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cat_str
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col_name
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X_profile
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[ 1.741842269897461, 0, 3, 0.5934939980506897, -0.8570905923843384, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 58, 0, 3, 1110669.75, 1, 0, 0, 1, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 58.0; gender: female; income: more than 15L; balance: 1110669.75; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 58-year-old female with an income of more than 15L. She has a balance of 1110669.75 and a vintage of 1.0. Her transaction status is 0.0 and she currently holds 1 product. She has 1 credit card, but her credit type is poor."
[ -0.8394641280174255, 1, 0, -0.7647924423217773, 0.5140069723129272, -1.0320936441421509, 0, 0.7107784152030945, 1 ]
[ 33, 1, 0, 410179.59375, 3, 0, 0, 1, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 33.0; gender: male; income: 10L-15L; balance: 410179.59375; vintage: 3.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 33-year-old male with an annual income of 10L-15L. He currently has a balance of 410179.59375 and has been a customer for 3.0 years. His transaction status is 0.0 and he holds 1 product. He also has 1 credit card and has a good credit type."
[ -0.2199505865573883, 0, 0, 0.8068997263908386, -0.17154182493686676, 0.9689042568206787, 0, 0.7107784152030945, 0 ]
[ 39, 0, 0, 1220726.5, 2, 1, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: female; income: 10L-15L; balance: 1220726.5; vintage: 2.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 39-year-old female with an annual income of 10L-15L. She currently has a balance of 1220726.5 and has been a customer for 2.0 years with a transaction status of 1.0. She holds 1 product and has 1 credit card with an average credit type."
[ 0.6060674786567688, 1, 0, -1.1163029670715332, -0.8570905923843384, -1.0320936441421509, 1, 0.7107784152030945, 0 ]
[ 47, 1, 0, 228899.96875, 1, 0, 1, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 47.0; gender: male; income: 10L-15L; balance: 228899.96875; vintage: 1.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 47-year-old male with an annual income of 10L-15L. He has a balance of 228899.96875 and a vintage of 1.0. His transaction status is 0.0 and he currently holds 2 products, including 1 credit card. The credit card he holds is of average credit type."
[ -0.11669833958148956, 1, 1, 2.203174591064453, -1.5426393747329712, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 40, 1, 1, 1940808, 0, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 40.0; gender: male; income: 5L-10L; balance: 1940808.0; vintage: 0.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 40-year-old male with an income between 5L-10L. He currently has a balance of 1940808.0 and a vintage of 0.0. His transaction status is 0.0 and he holds 2 product holdings, including 1 credit card. However, his credit type is poor."
[ 2.154851198196411, 0, 0, -1.4720567464828491, -0.8570905923843384, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 62, 0, 0, 45432, 1, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 62.0; gender: female; income: 10L-15L; balance: 45432.0; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 62-year-old female with an income of 10L-15L. She has a balance of 45432.0 and a vintage of 1.0. Her transaction status is 1.0 and she currently holds 2 products. She has 1 credit card, but her credit type is poor."
[ 1.3288332223892212, 1, 1, -0.10619640350341797, 0.5140069723129272, 0.9689042568206787, 0, 0.7107784152030945, 2 ]
[ 54, 1, 1, 749828.1875, 3, 1, 0, 1, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 54.0; gender: male; income: 5L-10L; balance: 749828.1875; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 54-year-old male with an income between 5L-10L. He has a balance of 749828.1875 and a vintage of 3.0. His transaction status is 1.0 and he currently holds 1 product. He also has a credit card with a credit type of poor."
[ 2.258103609085083, 1, 1, -0.34917452931404114, 1.19955575466156, 0.9689042568206787, 1, -1.4069081544876099, 2 ]
[ 63, 1, 1, 624520.4375, 4, 1, 1, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 63.0; gender: male; income: 5L-10L; balance: 624520.4375; vintage: 4.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: poor;"
"This customer is a 63-year-old male with an income between 5L-10L. He has a balance of 624520.4375 and a vintage of 4.0. His transaction status is 1.0 and he currently holds 2 products. He does not have a credit card and his credit type is poor."
[ 1.8450945615768433, 0, 3, 0.6234258413314819, 1.19955575466156, 0.9689042568206787, 0, 0.7107784152030945, 2 ]
[ 59, 0, 3, 1126106.125, 4, 1, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 59.0; gender: female; income: more than 15L; balance: 1126106.125; vintage: 4.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 59-year-old female with an income of more than 15L. She has a balance of 1126106.125 and a vintage of 4.0. Her transaction status is 1.0 and she currently holds 1 product. She has 1 credit card, but her credit type is poor."
[ -0.32320284843444824, 1, 3, -0.8287904262542725, -0.17154182493686676, 0.9689042568206787, 0, 0.7107784152030945, 0 ]
[ 38, 1, 3, 377174.78125, 2, 1, 0, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 38.0; gender: male; income: more than 15L; balance: 377174.78125; vintage: 2.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 38-year-old male with an income of more than 15L. He has a balance of 377174.78125 and a vintage of 2.0. His transaction status is 1.0 and he holds 1 product. He has 1 credit card with an average credit type."
[ 1.741842269897461, 0, 1, -0.7312622666358948, 0.5140069723129272, -1.0320936441421509, 1, 0.7107784152030945, 0 ]
[ 58, 0, 1, 427471.65625, 3, 0, 1, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 58.0; gender: female; income: 5L-10L; balance: 427471.65625; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 58-year-old female with an annual income of 5L-10L. She has a balance of 427471.65625 and has been a customer for 3 years. Her transaction status is currently at 0.0. She holds 2 products, including 1 credit card with an average credit type."
[ 0.19305843114852905, 1, 0, 0.7325287461280823, 1.19955575466156, -1.0320936441421509, 1, -1.4069081544876099, 0 ]
[ 43, 1, 0, 1182372.25, 4, 0, 1, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 43.0; gender: male; income: 10L-15L; balance: 1182372.25; vintage: 4.0; transaction status: 0.0; product holdings: 2; credit card: 0.0; credit type: average;"
"This customer is a 43-year-old male with an income of 10L-15L. He has a balance of 1182372.25 and a vintage of 4.0. His transaction status is 0.0 and he currently holds 2 products. He does not have a credit card and his credit type is average."
[ -1.1492209434509277, 0, 3, 1.0425931215286255, -0.8570905923843384, 0.9689042568206787, 1, -1.4069081544876099, 2 ]
[ 30, 0, 3, 1342277.375, 1, 1, 1, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 30.0; gender: female; income: more than 15L; balance: 1342277.375; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: poor;"
"This customer is a 30-year-old female with an income of more than 15L. She has a balance of 1342277.375 and a vintage of 1.0. Her transaction status is 1.0 and she currently holds 2 products. She does not have a credit card and her credit type is poor."
[ 0.6060674786567688, 0, 1, 0.5349774956703186, -1.5426393747329712, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 47, 0, 1, 1080491.875, 0, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 47.0; gender: female; income: 5L-10L; balance: 1080491.875; vintage: 0.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 47-year-old female with an income between 5L-10L. She currently has a balance of 1080491.875 and a vintage of 0.0. Her transaction status is 1.0, indicating that she is an active user. She holds 2 products, including 1 credit card. However, her credit type is poor."
[ 1.122328758239746, 1, 0, 0.11842642724514008, -0.8570905923843384, 0.9689042568206787, 0, 0.7107784152030945, 0 ]
[ 52, 1, 0, 865669.75, 1, 1, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 52.0; gender: male; income: 10L-15L; balance: 865669.75; vintage: 1.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 52-year-old male with an annual income of 10L-15L. He has a balance of 865669.75 and has been a customer for 1.0 year. His transaction status is 1.0 and he currently holds 1 product. He also has 1 credit card with an average credit type."
[ -0.736211895942688, 1, 0, -1.1083076000213623, 0.5140069723129272, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 34, 1, 0, 233023.3125, 3, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 34.0; gender: male; income: 10L-15L; balance: 233023.3125; vintage: 3.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 34-year-old male with an income of 10L-15L. He has a balance of 233023.3125 and a vintage of 3.0. His transaction status is 1.0 and he currently holds 2 products, including 1 credit card. However, his credit type is poor."
[ -0.32320284843444824, 0, 3, 0.14855323731899261, -1.5426393747329712, -1.0320936441421509, 1, 0.7107784152030945, 0 ]
[ 38, 0, 3, 881206.625, 0, 0, 1, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 38.0; gender: female; income: more than 15L; balance: 881206.625; vintage: 0.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 38-year-old female with an income of more than 15L. She currently has a balance of 881206.625 and a vintage of 0.0. Her transaction status is also 0.0. She holds 2 products, including 1 credit card with an average credit type."
[ -0.9427163600921631, 1, 0, -0.09176108241081238, 1.19955575466156, -1.0320936441421509, 1, 0.7107784152030945, 0 ]
[ 32, 1, 0, 757272.6875, 4, 0, 1, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 32.0; gender: male; income: 10L-15L; balance: 757272.6875; vintage: 4.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 32-year-old male with an income of 10L-15L. He has a balance of 757272.6875 and a vintage of 4.0. His transaction status is 0.0 and he currently holds 2 products, including 1 credit card. His credit type is average."
[ 2.5678603649139404, 1, 0, -1.1533923149108887, -1.5426393747329712, 0.9689042568206787, 1, 0.7107784152030945, 0 ]
[ 66, 1, 0, 209772.359375, 0, 1, 1, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 66.0; gender: male; income: 10L-15L; balance: 209772.359375; vintage: 0.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 66-year-old male with an income of 10L-15L. He currently has a balance of 209772.359375 and a vintage of 0.0. His transaction status is 1.0, indicating that he is an active user. He holds 2 products, including 1 credit card with an average credit type."
[ -0.6329596042633057, 0, 0, -1.4008198976516724, -0.8570905923843384, 0.9689042568206787, 1, -1.4069081544876099, 2 ]
[ 35, 0, 0, 82170, 1, 1, 1, 0, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 35.0; gender: female; income: 10L-15L; balance: 82170.0; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: poor;"
"This customer is a 35-year-old female with an income of 10L-15L. She currently has a balance of 82170.0 and a vintage of 1.0. Her transaction status is 1.0 and she holds 2 product holdings. She does not have a credit card and her credit type is poor."
[ 0.39956292510032654, 1, 0, -1.4503296613693237, 1.19955575466156, 0.9689042568206787, 1, -1.4069081544876099, 1 ]
[ 45, 1, 0, 56637, 4, 1, 1, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 45.0; gender: male; income: 10L-15L; balance: 56637.0; vintage: 4.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: good;"
"This customer is a 45-year-old male with an annual income of 10L-15L. He currently has a balance of 56637.0 and has been a customer for 4.0 years. His transaction status is 1.0, indicating that he is an active user. He holds 2 products but does not have a credit card. His credit type is good."
[ 0.19305843114852905, 0, 1, 0.006184730678796768, -0.17154182493686676, 0.9689042568206787, 1, 0.7107784152030945, 1 ]
[ 43, 0, 1, 807784.9375, 2, 1, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 43.0; gender: female; income: 5L-10L; balance: 807784.9375; vintage: 2.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 43-year-old female with an annual income of 5L-10L. She has a healthy balance of 807784.9375 and has been a customer for 2 years. Her transaction status is 1.0, indicating that she is an active user of the financial services. She currently holds 2 products and has 1 credit card with a good credit type."
[ -0.736211895942688, 0, 2, -1.23223876953125, -1.5426393747329712, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 34, 0, 2, 169110, 0, 0, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 34.0; gender: female; income: less than 5L; balance: 169110.0; vintage: 0.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 34-year-old female with an income of less than 5L. She currently has a balance of 169110.0 and a vintage of 0.0. Her transaction status is 0.0 and she holds 1 product. She has 1 credit card with an average credit type."
[ -1.562229871749878, 1, 2, 0.7465112209320068, 1.19955575466156, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 26, 1, 2, 1189583.25, 4, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 26.0; gender: male; income: less than 5L; balance: 1189583.25; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 26-year-old male with an income of less than 5L. He has a balance of 1189583.25 and a vintage of 4.0. His transaction status is 0.0 and he currently holds 1 product. He has 1 credit card with a poor credit type."
[ 0.19305843114852905, 0, 3, -0.948952853679657, -1.5426393747329712, -1.0320936441421509, 1, 0.7107784152030945, 1 ]
[ 43, 0, 3, 315205.125, 0, 0, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 43.0; gender: female; income: more than 15L; balance: 315205.125; vintage: 0.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 43-year-old female with an income of more than 15L. She currently has a balance of 315205.125 and a vintage of 0.0. Her transaction status is also at 0.0. She holds 2 product holdings, including 1 credit card. Her credit type is good."
[ -0.736211895942688, 0, 3, 0.0732164978981018, 0.5140069723129272, 0.9689042568206787, 0, -1.4069081544876099, 1 ]
[ 34, 0, 3, 842354.25, 3, 1, 0, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 34.0; gender: female; income: more than 15L; balance: 842354.25; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 0.0; credit type: good;"
"This customer is a 34-year-old female with an income of more than 15L. She has a balance of 842354.25 and a vintage of 3.0. Her transaction status is 1.0 and she currently holds 1 product. She does not have a credit card, but her credit type is good."
[ -0.6329596042633057, 0, 2, -0.13069355487823486, 1.19955575466156, 0.9689042568206787, 1, 0.7107784152030945, 0 ]
[ 35, 0, 2, 737194.5625, 4, 1, 1, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 35.0; gender: female; income: less than 5L; balance: 737194.5625; vintage: 4.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 35-year-old female with an income of less than 5L. She has a balance of 737194.5625 and a vintage of 4.0. Her transaction status is 1.0 and she currently holds 2 products, including 1 credit card. Her credit type is average."
[ 1.3288332223892212, 1, 2, 0.40754812955856323, 0.5140069723129272, -1.0320936441421509, 1, 0.7107784152030945, 1 ]
[ 54, 1, 2, 1014774.5, 3, 0, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 54.0; gender: male; income: less than 5L; balance: 1014774.5; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 54-year-old male with an income of less than 5L. He has a balance of 1014774.5 and a vintage of 3.0. His transaction status is 0.0 and he currently holds 2 products. He has 1 credit card and his credit type is good."
[ 1.8450945615768433, 1, 0, -0.25343963503837585, -1.5426393747329712, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 59, 1, 0, 673892.4375, 0, 1, 0, 1, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 59.0; gender: male; income: 10L-15L; balance: 673892.4375; vintage: 0.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 59-year-old male with an annual income of 10L-15L. He currently has a balance of 673892.4375 in his account and has been a customer for 0.0 years. His transaction status is 1.0, indicating that he is an active user. He holds one product and has one credit card with a good credit type."
[ 0.7093197107315063, 1, 1, -0.8701497316360474, -1.5426393747329712, 0.9689042568206787, 1, -1.4069081544876099, 2 ]
[ 48, 1, 1, 355845.15625, 0, 1, 1, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: male; income: 5L-10L; balance: 355845.15625; vintage: 0.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: poor;"
"This customer is a 48-year-old male with an income between 5L-10L. He currently has a balance of 355845.15625 and a vintage of 0.0. His transaction status is 1.0 and he holds 2 product holdings. He does not have a credit card and his credit type is poor."
[ 0.08980616927146912, 1, 0, 1.7689518928527832, -0.8570905923843384, 0.9689042568206787, 0, 0.7107784152030945, 2 ]
[ 42, 1, 0, 1716872.25, 1, 1, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 42.0; gender: male; income: 10L-15L; balance: 1716872.25; vintage: 1.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 42-year-old male with an income of 10L-15L. He has a balance of 1716872.25 and a vintage of 1.0. His transaction status is 1.0 and he currently holds 1 product. He has 1 credit card with a poor credit type."
[ -1.2524731159210205, 0, 0, 0.18887117505073547, 0.5140069723129272, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 29, 0, 0, 901999.25, 3, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 29.0; gender: female; income: 10L-15L; balance: 901999.25; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 29-year-old female with an annual income of 10L-15L. She currently has a balance of 901999.25 and has been a customer for 3 years. Her transaction status is 0.0, indicating that she has not made any recent transactions. She holds 2 products, including 1 credit card. Her credit type is poor."
[ 0.5028151869773865, 0, 1, -1.3422527313232422, 0.5140069723129272, 0.9689042568206787, 0, -1.4069081544876099, 1 ]
[ 46, 0, 1, 112374, 3, 1, 0, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 46.0; gender: female; income: 5L-10L; balance: 112374.0; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 0.0; credit type: good;"
"This customer is a 46-year-old female with an annual income of 5L-10L. She currently has a balance of 112374.0 and has been a customer for 3.0 years with a transaction status of 1.0. She holds 1 product and does not have a credit card. Her credit type is good."
[ -0.5297073721885681, 0, 0, 1.1564487218856812, -0.8570905923843384, 0.9689042568206787, 0, -1.4069081544876099, 0 ]
[ 36, 0, 0, 1400994.5, 1, 1, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 36.0; gender: female; income: 10L-15L; balance: 1400994.5; vintage: 1.0; transaction status: 1.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 36-year-old female with an annual income of 10L-15L. She currently has a balance of 1400994.5 and has been a customer for 1.0 year with a transaction status of 1.0. She holds 1 product but does not have a credit card. Her credit type is average."
[ -1.3557254076004028, 0, 3, -1.5047084093093872, 0.5140069723129272, -1.0320936441421509, 1, -1.4069081544876099, 2 ]
[ 28, 0, 3, 28593, 3, 0, 1, 0, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 28.0; gender: female; income: more than 15L; balance: 28593.0; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 0.0; credit type: poor;"
"This customer is a 28-year-old female with an income of more than 15L. She has a balance of 28593.0 and a vintage of 3.0. Her transaction status is 0.0 and she currently holds 2 products. She does not have a credit card and her credit type is poor."
[ -1.562229871749878, 1, 1, 1.3737752437591553, 0.5140069723129272, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 26, 1, 1, 1513073.375, 3, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 26.0; gender: male; income: 5L-10L; balance: 1513073.375; vintage: 3.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 26-year-old male with an income between 5L-10L. He currently has a balance of 1513073.375 and has been a customer for 3.0 years. His transaction status is 0.0 and he currently holds 1 product. He has 1 credit card, but his credit type is poor."
[ 0.19305843114852905, 0, 3, -0.7198798656463623, -0.17154182493686676, 0.9689042568206787, 2, -1.4069081544876099, 2 ]
[ 43, 0, 3, 433341.71875, 2, 1, 2, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 43.0; gender: female; income: more than 15L; balance: 433341.71875; vintage: 2.0; transaction status: 1.0; product holdings: 3+; credit card: 0.0; credit type: poor;"
"This customer is a 43-year-old female with an income of more than 15L. She has a balance of 433341.71875 and a vintage of 2.0. Her transaction status is 1.0 and she holds 3 or more products. She does not have a credit card and her credit type is poor."
[ -0.4264551103115082, 0, 3, 0.7270142436027527, 0.5140069723129272, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 37, 0, 3, 1179528.25, 3, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 37.0; gender: female; income: more than 15L; balance: 1179528.25; vintage: 3.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 37-year-old female with an income of more than 15L. She has a balance of 1179528.25 and a vintage of 3.0. Her transaction status is 1.0 and she currently holds 2 products. She has 1 credit card, but her credit type is poor."
[ 0.296310693025589, 1, 1, 1.5698474645614624, -0.17154182493686676, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 44, 1, 1, 1614191, 2, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 44.0; gender: male; income: 5L-10L; balance: 1614191.0; vintage: 2.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 44-year-old male with an income between 5L-10L. He currently has a balance of 1614191.0 and a vintage of 2.0. His transaction status is 0.0 and he holds 2 product holdings, including 1 credit card. However, his credit type is poor."
[ -0.2199505865573883, 1, 3, -0.5455060601234436, -0.8570905923843384, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 39, 1, 3, 523269.09375, 1, 0, 0, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: male; income: more than 15L; balance: 523269.09375; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 39-year-old male with an income of more than 15L. He has a balance of 523269.09375 and a vintage of 1.0. His transaction status is 0.0 and he currently holds 1 product. He has 1 credit card with an average credit type."
[ -0.5297073721885681, 1, 1, -1.5408952236175537, 0.5140069723129272, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 36, 1, 1, 9930.8701171875, 3, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 36.0; gender: male; income: 5L-10L; balance: 9930.8701171875; vintage: 3.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 36-year-old male with an income between 5L-10L. He has a balance of 9930.8701171875 and has been a customer for 3.0 years. His transaction status is 1.0, indicating he is an active user. He currently holds 2 products, including 1 credit card. However, his credit type is poor."
[ -1.4589776992797852, 1, 1, -0.588887095451355, 1.19955575466156, -1.0320936441421509, 1, 0.7107784152030945, 1 ]
[ 27, 1, 1, 500896.8125, 4, 0, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 27.0; gender: male; income: 5L-10L; balance: 500896.8125; vintage: 4.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 27-year-old male with an annual income between 5 and 10 lakhs. He currently has a balance of 500,896.81 rupees and has been a customer for 4 years. His transaction status is currently at 0.0 and he holds 2 products, including 1 credit card. His credit type is good."
[ -0.9427163600921631, 1, 2, -0.4484398365020752, 0.5140069723129272, -1.0320936441421509, 1, 0.7107784152030945, 1 ]
[ 32, 1, 2, 573327.75, 3, 0, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 32.0; gender: male; income: less than 5L; balance: 573327.75; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 32-year-old male with an income of less than 5L. He has a balance of 573327.75 and a vintage of 3.0. His transaction status is 0.0 and he currently holds 2 products, including 1 credit card. His credit type is good."
[ 0.7093197107315063, 1, 0, -0.019299639388918877, -0.8570905923843384, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 48, 1, 0, 794642.25, 1, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: male; income: 10L-15L; balance: 794642.25; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 48-year-old male with an income between 10L-15L. He currently has a balance of 794642.25 and a vintage of 1.0. His transaction status is 0.0 and he holds 1 product. He has 1 credit card with a poor credit type."
[ -0.9427163600921631, 1, 0, -0.9226388335227966, -0.8570905923843384, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 32, 1, 0, 328775.65625, 1, 1, 0, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 32.0; gender: male; income: 10L-15L; balance: 328775.65625; vintage: 1.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 32-year-old male with an annual income of 10L-15L. He has a healthy account balance of 328775.65625 and has been a customer for 1 year. His transaction status is 1.0, indicating he is an active user. He currently holds 1 product and has a good credit score, with 1 credit card in his possession."
[ 0.7093197107315063, 0, 2, -1.2230031490325928, -0.8570905923843384, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 48, 0, 2, 173872.984375, 1, 0, 0, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: female; income: less than 5L; balance: 173872.984375; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 48-year-old female with an income of less than 5L. She has a balance of 173872.984375 and a vintage of 1.0. Her transaction status is 0.0 and she currently holds 1 product. She has 1 credit card with an average credit type."
[ -0.4264551103115082, 0, 3, 2.3112447261810303, -0.17154182493686676, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 37, 0, 3, 1996541.5, 2, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 37.0; gender: female; income: more than 15L; balance: 1996541.5; vintage: 2.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 37-year-old female with an income of more than 15L. She has a balance of 1996541.5 and a vintage of 2.0. Her transaction status is 0.0 and she currently holds 1 product. She has 1 credit card with a poor credit type."
[ 1.0190764665603638, 0, 1, -1.3553065061569214, 1.19955575466156, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 51, 0, 1, 105642, 4, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 51.0; gender: female; income: 5L-10L; balance: 105642.0; vintage: 4.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 51-year-old female with an income between 5L-10L. She currently has a balance of 105642.0 and has been a customer for 4.0 years. Her transaction status is 0.0 and she holds 2 products, including 1 credit card. Her credit type is poor."
[ -0.6329596042633057, 1, 1, 0.7998109459877014, 0.5140069723129272, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 35, 1, 1, 1217070.75, 3, 1, 0, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 35.0; gender: male; income: 5L-10L; balance: 1217070.75; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 35-year-old male with an income between 5L-10L. He has a healthy balance of 1217070.75 and has been a customer for 3.0 years. His transaction status is 1.0, indicating he is an active user. He currently holds 1 product and has 1 credit card with a good credit type."
[ 2.5678603649139404, 0, 3, 0.5624043941497803, 0.5140069723129272, 0.9689042568206787, 0, 0.7107784152030945, 2 ]
[ 66, 0, 3, 1094636.375, 3, 1, 0, 1, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 66.0; gender: female; income: more than 15L; balance: 1094636.375; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 66-year-old female with an income of more than 15L. She has a balance of 1094636.375 and a vintage of 3.0. Her transaction status is 1.0 and she currently holds 1 product. She has 1 credit card with a poor credit type."
[ 1.0190764665603638, 0, 0, 0.9454337954521179, -1.5426393747329712, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 51, 0, 0, 1292170.75, 0, 1, 0, 1, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 51.0; gender: female; income: 10L-15L; balance: 1292170.75; vintage: 0.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 51-year-old female with an annual income of 10L-15L. She currently has a balance of 1292170.75 in her account and has been a customer for 0.0 years. Her transaction status is 1.0, indicating that she is an active user of the bank's services. She holds one product with the bank and has one credit card with a good credit type."
[ -0.6329596042633057, 0, 3, 1.1656057834625244, -0.17154182493686676, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 35, 0, 3, 1405717, 2, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 35.0; gender: female; income: more than 15L; balance: 1405717.0; vintage: 2.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 35-year-old female with an income of more than 15L. She has a balance of 1405717.0 and a vintage of 2.0. Her transaction status is 0.0 and she currently holds 2 products. She has 1 credit card, but her credit type is poor."
[ 0.8125719428062439, 1, 2, -0.7853204011917114, -1.5426393747329712, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 49, 1, 2, 399592.96875, 0, 1, 0, 1, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 49.0; gender: male; income: less than 5L; balance: 399592.96875; vintage: 0.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 49-year-old male with an income of less than 5L. He has a balance of 399592.96875 and a vintage of 0.0. His transaction status is 1.0 and he holds 1 product. He also has a credit card with a good credit type."
[ 1.122328758239746, 0, 1, -0.7795220017433167, -0.17154182493686676, 0.9689042568206787, 1, 0.7107784152030945, 0 ]
[ 52, 0, 1, 402583.3125, 2, 1, 1, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 52.0; gender: female; income: 5L-10L; balance: 402583.3125; vintage: 2.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 52-year-old female with an annual income of 5L-10L. She has a balance of 402583.3125 and has been a customer for 2 years. Her transaction status is 1.0, indicating that she is an active user. She currently holds 2 products, including 1 credit card with an average credit type."
[ -0.013446083292365074, 0, 2, 1.5099835395812988, -0.17154182493686676, -1.0320936441421509, 0, 0.7107784152030945, 1 ]
[ 41, 0, 2, 1583318.125, 2, 0, 0, 1, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 41.0; gender: female; income: less than 5L; balance: 1583318.125; vintage: 2.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 41-year-old female with an income of less than 5L. She has a balance of 1583318.125 and a vintage of 2.0. Her transaction status is 0.0 and she currently holds 1 product. She has 1 credit card and her credit type is good."
[ -1.1492209434509277, 1, 0, 1.571873426437378, 1.19955575466156, -1.0320936441421509, 0, -1.4069081544876099, 2 ]
[ 30, 1, 0, 1615235.75, 4, 0, 0, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 30.0; gender: male; income: 10L-15L; balance: 1615235.75; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: poor;"
"The customer is a 30-year-old male with an income of 10L-15L. He has a balance of 1615235.75 and a vintage of 4.0. His transaction status is 0.0 and he currently holds 1 product. He does not have a credit card and his credit type is poor."
[ 0.39956292510032654, 1, 1, -0.14616234600543976, 1.8851045370101929, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 45, 1, 1, 729217.0625, 5, 0, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 45.0; gender: male; income: 5L-10L; balance: 729217.0625; vintage: 5.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 45-year-old male with an income between 5L-10L. He has a balance of 729217.0625 and a vintage of 5.0. His transaction status is 0.0 and he currently holds 1 product. He does not have a credit card and his credit type is average."
[ 1.2255809307098389, 1, 3, -1.3146969079971313, -0.17154182493686676, 0.9689042568206787, 1, -1.4069081544876099, 1 ]
[ 53, 1, 3, 126585, 2, 1, 1, 0, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 53.0; gender: male; income: more than 15L; balance: 126585.0; vintage: 2.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: good;"
"This customer is a 53-year-old male with an income of more than 15L. He has a balance of 126585.0 and a vintage of 2.0. His transaction status is 1.0 and he currently holds 2 products. He does not have a credit card, but his credit type is good."
[ -0.9427163600921631, 0, 2, 1.1047073602676392, -0.17154182493686676, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 32, 0, 2, 1374310.75, 2, 0, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 32.0; gender: female; income: less than 5L; balance: 1374310.75; vintage: 2.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 32-year-old female with an income of less than 5L. She has a balance of 1374310.75 and a vintage of 2.0. Her transaction status is 0.0 and she currently holds 1 product. She has 1 credit card with an average credit type."
[ -1.1492209434509277, 0, 3, -1.5529268980026245, 1.8851045370101929, 0.9689042568206787, 1, 0.7107784152030945, 0 ]
[ 30, 0, 3, 3726, 5, 1, 1, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 30.0; gender: female; income: more than 15L; balance: 3726.0; vintage: 5.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 30-year-old female with an income of more than 15L. She has a balance of 3726.0 and a vintage of 5.0. Her transaction status is 1.0 and she currently holds 2 products, including 1 credit card. The credit card she holds is of average credit type."
[ 0.08980616927146912, 1, 2, -0.7280250191688538, -0.17154182493686676, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 42, 1, 2, 429141.15625, 2, 1, 0, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 42.0; gender: male; income: less than 5L; balance: 429141.15625; vintage: 2.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 42-year-old male with an income of less than 5L. He has a balance of 429141.15625 and a vintage of 2.0. His transaction status is 1.0 and he holds 1 product. He has a credit card with a good credit type."
[ 0.19305843114852905, 1, 1, -0.1233820840716362, 0.5140069723129272, 0.9689042568206787, 1, -1.4069081544876099, 2 ]
[ 43, 1, 1, 740965.25, 3, 1, 1, 0, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 43.0; gender: male; income: 5L-10L; balance: 740965.25; vintage: 3.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: poor;"
"This customer is a 43-year-old male with an income between 5L-10L. He has a balance of 740965.25 and a vintage of 3.0. His transaction status is 1.0 and he currently holds 2 products. He does not have a credit card and his credit type is poor."
[ 1.3288332223892212, 0, 2, 0.10494028776884079, -0.8570905923843384, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 54, 0, 2, 858714.75, 1, 0, 1, 1, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 54.0; gender: female; income: less than 5L; balance: 858714.75; vintage: 1.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 54-year-old female with an income of less than 5L. She has a balance of 858714.75 and a vintage of 1.0. Her transaction status is 0.0 and she currently holds 2 products. She has 1 credit card, but her credit type is poor."
[ 0.7093197107315063, 1, 0, 1.9654866456985474, -0.8570905923843384, 0.9689042568206787, 1, 0.7107784152030945, 0 ]
[ 48, 1, 0, 1818228.375, 1, 1, 1, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: male; income: 10L-15L; balance: 1818228.375; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 48-year-old male with an annual income of 10L-15L. He has a healthy balance of 1818228.375 and has been a customer for 1.0 year with a transaction status of 1.0. He currently holds 2 products and has 1 credit card with an average credit type."
[ 0.7093197107315063, 0, 1, -0.18601363897323608, 0.5140069723129272, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 48, 0, 1, 708665.125, 3, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: female; income: 5L-10L; balance: 708665.125; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 48-year-old female with an income between 5L-10L. She currently has a balance of 708665.125 and has been a customer for 3.0 years. Her transaction status is 0.0 and she holds 2 product holdings, including 1 credit card. Her credit type is poor."
[ -1.3557254076004028, 0, 0, -1.0352362394332886, -0.8570905923843384, -1.0320936441421509, 1, -1.4069081544876099, 0 ]
[ 28, 0, 0, 270707.40625, 1, 0, 1, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 28.0; gender: female; income: 10L-15L; balance: 270707.40625; vintage: 1.0; transaction status: 0.0; product holdings: 2; credit card: 0.0; credit type: average;"
"This customer is a 28-year-old female with an annual income of 10L-15L. She currently has a balance of 270707.40625 and a vintage of 1.0. Her transaction status is 0.0 and she holds 2 product holdings. She does not have a credit card and her credit type is average."
[ 0.9158242344856262, 0, 3, 0.01119120605289936, -0.8570905923843384, 0.9689042568206787, 1, 0.7107784152030945, 1 ]
[ 50, 0, 3, 810366.8125, 1, 1, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 50.0; gender: female; income: more than 15L; balance: 810366.8125; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 50-year-old female with an income of more than 15L. She has a balance of 810366.8125 and a vintage of 1.0. Her transaction status is 1.0 and she currently holds 2 products. She has 1 credit card with a good credit type."
[ 2.361355781555176, 1, 2, -0.07449407875537872, 0.5140069723129272, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 64, 1, 2, 766177.5625, 3, 0, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 64.0; gender: male; income: less than 5L; balance: 766177.5625; vintage: 3.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 64-year-old male with an income of less than 5L. He has a balance of 766177.5625 and a vintage of 3.0. His transaction status is 0.0 and he currently holds 1 product. He does not have a credit card and his credit type is average."
[ -0.9427163600921631, 0, 0, -0.44611912965774536, 1.19955575466156, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 32, 0, 0, 574524.5625, 4, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 32.0; gender: female; income: 10L-15L; balance: 574524.5625; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 32-year-old female with an income of 10L-15L. She has a balance of 574524.5625 and a vintage of 4.0. Her transaction status is 0.0 and she currently holds 1 product. She has 1 credit card, but her credit type is poor."
[ 0.19305843114852905, 1, 2, 0.8101085424423218, 1.19955575466156, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 43, 1, 2, 1222381.375, 4, 0, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 43.0; gender: male; income: less than 5L; balance: 1222381.375; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 43-year-old male with an income of less than 5L. He has a balance of 1222381.375 and a vintage of 4.0. His transaction status is 0.0 and he currently holds 1 product. He does not have a credit card and his credit type is average."
[ 0.08980616927146912, 1, 1, 1.1550029516220093, 0.5140069723129272, -1.0320936441421509, 1, 0.7107784152030945, 1 ]
[ 42, 1, 1, 1400249, 3, 0, 1, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 42.0; gender: male; income: 5L-10L; balance: 1400249.0; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: good;"
"This customer is a 42-year-old male with an annual income between 5L-10L. He currently has a balance of 1400249.0 and has been a customer for 3.0 years. His transaction status is 0.0 and he holds 2 products, including 1 credit card. His credit type is good."
[ 1.0190764665603638, 0, 3, -0.4044380486011505, 1.19955575466156, -1.0320936441421509, 1, 0.7107784152030945, 0 ]
[ 51, 0, 3, 596020.125, 4, 0, 1, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 51.0; gender: female; income: more than 15L; balance: 596020.125; vintage: 4.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 51-year-old female with an income of more than 15L. She has a balance of 596020.125 and a vintage of 4.0. Her transaction status is 0.0 and she currently holds 2 products, including 1 credit card. Her credit type is average."
[ 0.7093197107315063, 1, 2, -1.1314953565597534, 0.5140069723129272, -1.0320936441421509, 1, -1.4069081544876099, 0 ]
[ 48, 1, 2, 221065.015625, 3, 0, 1, 0, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: male; income: less than 5L; balance: 221065.015625; vintage: 3.0; transaction status: 0.0; product holdings: 2; credit card: 0.0; credit type: average;"
"This customer is a 48-year-old male with an income of less than 5L. He has a balance of 221065.015625 and a vintage of 3.0. His transaction status is 0.0 and he currently holds 2 products. He does not have a credit card and his credit type is average."
[ 0.9158242344856262, 1, 0, -0.67437344789505, -0.17154182493686676, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 50, 1, 0, 456810.125, 2, 0, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 50.0; gender: male; income: 10L-15L; balance: 456810.125; vintage: 2.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 50-year-old male with an income of 10L-15L. He has a balance of 456810.125 and a vintage of 2.0. His transaction status is 0.0 and he currently holds 1 product. He has 1 credit card with an average credit type."
[ 0.7093197107315063, 0, 3, -0.33210909366607666, -1.5426393747329712, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 48, 0, 3, 633321.375, 0, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 48.0; gender: female; income: more than 15L; balance: 633321.375; vintage: 0.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 48-year-old female with an income of more than 15L. She currently has a balance of 633321.375 and a vintage of 0.0. Her transaction status is 1.0 and she holds 2 product holdings, including 1 credit card. However, her credit type is poor."
[ -0.32320284843444824, 0, 3, -0.06626414507627487, -0.8570905923843384, 0.9689042568206787, 1, -1.4069081544876099, 1 ]
[ 38, 0, 3, 770421.875, 1, 1, 1, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 38.0; gender: female; income: more than 15L; balance: 770421.875; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: good;"
"This customer is a 38-year-old female with an income of more than 15L. She has a balance of 770421.875 and a vintage of 1.0. Her transaction status is 1.0 and she currently holds 2 products. She does not have a credit card, but her credit type is good."
[ 0.8125719428062439, 1, 2, -0.64579176902771, -0.8570905923843384, 0.9689042568206787, 1, 0.7107784152030945, 0 ]
[ 49, 1, 2, 471550.125, 1, 1, 1, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 49.0; gender: male; income: less than 5L; balance: 471550.125; vintage: 1.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: average;"
"This customer is a 49-year-old male with an income of less than 5L. He has a balance of 471550.125 and a vintage of 1.0. His transaction status is 1.0 and he currently holds 2 products. He has 1 credit card with an average credit type."
[ -0.4264551103115082, 0, 1, -0.1423759013414383, 0.5140069723129272, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 37, 0, 1, 731169.8125, 3, 0, 0, 1, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 37.0; gender: female; income: 5L-10L; balance: 731169.8125; vintage: 3.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 37-year-old female with an income between 5L-10L. She currently has a balance of 731169.8125 and has been a customer for 3.0 years. Her transaction status is 0.0 and she holds 1 product. She has 1 credit card with an average credit type."
[ -0.11669833958148956, 0, 1, 1.0997556447982788, -0.17154182493686676, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 40, 0, 1, 1371757, 2, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 40.0; gender: female; income: 5L-10L; balance: 1371757.0; vintage: 2.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 40-year-old female with an income between 5L-10L. She currently has a balance of 1371757.0 and a vintage of 2.0. Her transaction status is 0.0 and she holds 1 product. She also has 1 credit card, but her credit type is poor."
[ -0.2199505865573883, 1, 1, -0.7521266937255859, -0.17154182493686676, -1.0320936441421509, 0, 0.7107784152030945, 2 ]
[ 39, 1, 1, 416711.53125, 2, 0, 0, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: male; income: 5L-10L; balance: 416711.53125; vintage: 2.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: poor;"
"This customer is a 39-year-old male with an income between 5L-10L. He currently has a balance of 416711.53125 and a vintage of 2.0. His transaction status is 0.0 and he holds 1 product. He has 1 credit card with a poor credit type."
[ -1.2524731159210205, 0, 0, -0.04968699812889099, -0.8570905923843384, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 29, 0, 0, 778971, 1, 0, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 29.0; gender: female; income: 10L-15L; balance: 778971.0; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 29-year-old female with an annual income of 10L-15L. She currently has a balance of 778971.0 and has been a customer for 1.0 year. Her transaction status is 0.0 and she holds 1 product. She has 1 credit card with an average credit type."
[ 0.296310693025589, 1, 0, 0.7681204676628113, -0.8570905923843384, -1.0320936441421509, 0, -1.4069081544876099, 1 ]
[ 44, 1, 0, 1200727.5, 1, 0, 0, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 44.0; gender: male; income: 10L-15L; balance: 1200727.5; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: good;"
"This customer is a 44-year-old male with an annual income of 10L-15L. He currently has a balance of 1200727.5 and a vintage of 1.0. His transaction status is 0.0 and he holds 1 product. He does not have a credit card and his credit type is good."
[ -0.11669833958148956, 1, 3, -0.2846972942352295, 0.5140069723129272, 0.9689042568206787, 0, 0.7107784152030945, 0 ]
[ 40, 1, 3, 657772.375, 3, 1, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 40.0; gender: male; income: more than 15L; balance: 657772.375; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 40-year-old male with an income of more than 15L. He has a balance of 657772.375 and a vintage of 3.0. His transaction status is 1.0 and he currently holds 1 product. He also has a credit card with an average credit type."
[ 1.122328758239746, 0, 1, 0.030783962458372116, -0.8570905923843384, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 52, 0, 1, 820471.125, 1, 0, 1, 1, 2 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 52.0; gender: female; income: 5L-10L; balance: 820471.125; vintage: 1.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 52-year-old female with an income between 5L-10L. She currently has a balance of 820471.125 and a vintage of 1.0. Her transaction status is 0.0 and she holds 2 product holdings, including 1 credit card. Her credit type is poor."
[ -0.2199505865573883, 0, 3, -0.023299340158700943, 1.19955575466156, 0.9689042568206787, 0, -1.4069081544876099, 1 ]
[ 39, 0, 3, 792579.5, 4, 1, 0, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: female; income: more than 15L; balance: 792579.5; vintage: 4.0; transaction status: 1.0; product holdings: 1; credit card: 0.0; credit type: good;"
"This customer is a 39-year-old female with an income of more than 15L. She has a balance of 792579.5 and a vintage of 4.0. Her transaction status is 1.0 and she currently holds 1 product. She does not have a credit card, but her credit type is good."
[ -0.4264551103115082, 1, 2, -0.7228310704231262, -1.5426393747329712, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 37, 1, 2, 431819.71875, 0, 0, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 37.0; gender: male; income: less than 5L; balance: 431819.71875; vintage: 0.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 37-year-old male with an income of less than 5L. He currently has a balance of 431819.71875 and a vintage of 0.0. His transaction status is also 0.0. He holds one product and does not have a credit card. His credit type is average."
[ -0.736211895942688, 1, 0, -1.2060984373092651, 1.8851045370101929, 0.9689042568206787, 1, -1.4069081544876099, 1 ]
[ 34, 1, 0, 182591.015625, 5, 1, 1, 0, 1 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 34.0; gender: male; income: 10L-15L; balance: 182591.015625; vintage: 5.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: good;"
"This customer is a 34-year-old male with an annual income of 10L-15L. He has a current balance of 182591.015625 and has been a customer for 5 years. His transaction status is 1.0, indicating he is an active user. He currently holds 2 products but does not have a credit card. His credit type is good."
[ 0.5028151869773865, 1, 1, -0.07798542082309723, 1.19955575466156, 0.9689042568206787, 0, 0.7107784152030945, 1 ]
[ 46, 1, 1, 764377, 4, 1, 0, 1, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 46.0; gender: male; income: 5L-10L; balance: 764377.0; vintage: 4.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: good;"
"This customer is a 46-year-old male with an annual income between 5L-10L. He has a healthy balance of 764377.0 and has been a customer for 4 years. His transaction status is 1.0, indicating he is an active user. He currently holds 1 product and has a good credit score, with 1 credit card."
[ -1.4589776992797852, 1, 3, -1.3665452003479004, -0.17154182493686676, 0.9689042568206787, 1, 0.7107784152030945, 2 ]
[ 27, 1, 3, 99846, 2, 1, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 27.0; gender: male; income: more than 15L; balance: 99846.0; vintage: 2.0; transaction status: 1.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 27-year-old male with an income of more than 15L. He has a balance of 99846.0 and a vintage of 2.0. His transaction status is 1.0 and he currently holds 2 products, including 1 credit card. However, his credit type is poor."
[ -0.2199505865573883, 1, 2, 1.3160995244979858, 1.19955575466156, -1.0320936441421509, 0, -1.4069081544876099, 1 ]
[ 39, 1, 2, 1483329, 4, 0, 0, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: male; income: less than 5L; balance: 1483329.0; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: good;"
"This customer is a 39-year-old male with an income of less than 5L. He has a balance of 1483329.0 and a vintage of 4.0. His transaction status is 0.0 and he holds 1 product. He does not have a credit card, but his credit type is good."
[ 0.39956292510032654, 1, 1, -1.432303547859192, 0.5140069723129272, 0.9689042568206787, 0, 0.7107784152030945, 0 ]
[ 45, 1, 1, 65933.3671875, 3, 1, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 45.0; gender: male; income: 5L-10L; balance: 65933.3671875; vintage: 3.0; transaction status: 1.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 45-year-old male with an income between 5L-10L. He has a balance of 65933.3671875 and has been a customer for 3.0 years. His transaction status is 1.0, indicating he is an active user. He currently holds 1 product and has 1 credit card. His credit type is average."
[ -1.1492209434509277, 1, 3, 0.6078174710273743, 0.5140069723129272, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 30, 1, 3, 1118056.625, 3, 0, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 30.0; gender: male; income: more than 15L; balance: 1118056.625; vintage: 3.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 30-year-old male with an income of more than 15L. He has a balance of 1118056.625 and a vintage of 3.0. His transaction status is 0.0 and he holds 1 product. He has 1 credit card with an average credit type."
[ 0.08980616927146912, 0, 1, 0.06988798081874847, -0.8570905923843384, -1.0320936441421509, 1, 0.7107784152030945, 2 ]
[ 42, 0, 1, 840637.6875, 1, 0, 1, 1, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 42.0; gender: female; income: 5L-10L; balance: 840637.6875; vintage: 1.0; transaction status: 0.0; product holdings: 2; credit card: 1.0; credit type: poor;"
"This customer is a 42-year-old female with an income between 5L-10L. She currently has a balance of 840637.6875 and a vintage of 1.0. Her transaction status is 0.0 and she holds 2 product holdings, including 1 credit card. Her credit type is poor."
[ 0.6060674786567688, 1, 0, 1.0922436714172363, -0.8570905923843384, 0.9689042568206787, 0, -1.4069081544876099, 2 ]
[ 47, 1, 0, 1367883, 1, 1, 0, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 47.0; gender: male; income: 10L-15L; balance: 1367883.0; vintage: 1.0; transaction status: 1.0; product holdings: 1; credit card: 0.0; credit type: poor;"
"This customer is a 47-year-old male with an income between 10L-15L. He has a balance of 1367883.0 and a vintage of 1.0. His transaction status is 1.0 and he currently holds 1 product. He does not have a credit card and his credit type is poor."
[ -0.2199505865573883, 0, 1, 0.022418081760406494, -1.5426393747329712, 0.9689042568206787, 1, -1.4069081544876099, 1 ]
[ 39, 0, 1, 816156.75, 0, 1, 1, 0, 1 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: female; income: 5L-10L; balance: 816156.75; vintage: 0.0; transaction status: 1.0; product holdings: 2; credit card: 0.0; credit type: good;"
"This customer is a 39-year-old female with an annual income between 5L-10L. She currently has a balance of 816156.75 in her account and has been a customer for 0.0 years. Her transaction status is 1.0, indicating that she is an active user. She holds 2 products with the bank and does not have a credit card. Her credit type is good."
[ -0.2199505865573883, 1, 1, 1.9721918106079102, 1.19955575466156, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 39, 1, 1, 1821686.375, 4, 0, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 39.0; gender: male; income: 5L-10L; balance: 1821686.375; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 39-year-old male with an income between 5L-10L. He currently has a balance of 1821686.375 and has been a customer for 4.0 years. His transaction status is 0.0 and he holds 1 product. He does not have a credit card and his credit type is average."
[ -0.9427163600921631, 1, 0, -0.8031350374221802, 0.5140069723129272, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 32, 1, 0, 390405.6875, 3, 0, 0, 0, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 32.0; gender: male; income: 10L-15L; balance: 390405.6875; vintage: 3.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 32-year-old male with an income between 10L-15L. He has a balance of 390405.6875 and a vintage of 3.0. His transaction status is 0.0 and he currently holds 1 product. He does not have a credit card and his credit type is average."
[ 0.6060674786567688, 1, 2, 1.6734552383422852, 1.19955575466156, -1.0320936441421509, 0, -1.4069081544876099, 0 ]
[ 47, 1, 2, 1667623.125, 4, 0, 0, 0, 0 ]
1
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 47.0; gender: male; income: less than 5L; balance: 1667623.125; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: average;"
"This customer is a 47-year-old male with an income of less than 5L. He has a balance of 1667623.125 and a vintage of 4.0. His transaction status is 0.0 and he currently holds 1 product. He does not have a credit card and his credit type is average."
[ -0.6329596042633057, 0, 2, -0.1803387701511383, -0.8570905923843384, -1.0320936441421509, 0, -1.4069081544876099, 2 ]
[ 35, 0, 2, 711591.75, 1, 0, 0, 0, 2 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 35.0; gender: female; income: less than 5L; balance: 711591.75; vintage: 1.0; transaction status: 0.0; product holdings: 1; credit card: 0.0; credit type: poor;"
"This customer is a 35-year-old female with an income of less than 5L. She currently has a balance of 711591.75 and a vintage of 1.0. Her transaction status is 0.0 and she holds 1 product. She does not have a credit card and her credit type is poor."
[ -1.0459686517715454, 0, 0, -1.0323537588119507, 1.19955575466156, -1.0320936441421509, 0, 0.7107784152030945, 0 ]
[ 31, 0, 0, 272193.9375, 4, 0, 0, 1, 0 ]
0
2
9
[ 0, 3, 4, 5, 7 ]
[ 1, 2, 6, 8 ]
[ 2, 4, 3, 3 ]
[ [ "female", "male" ], [ "10L-15L", "5L-10L", "less_than_5L", "more_than_15L" ], [ "1", "2", "3+" ], [ "average", "good", "poor" ] ]
[ "age", "gender", "income", "balance", "vintage", "transaction_status", "product_holdings", "credit_card", "credit_type" ]
"Construct a concise customer profile description including all the following information: age: 31.0; gender: female; income: 10L-15L; balance: 272193.9375; vintage: 4.0; transaction status: 0.0; product holdings: 1; credit card: 1.0; credit type: average;"
"This customer is a 31-year-old female with an annual income of 10L-15L. She currently has a balance of 272193.9375 and has been a customer for 4 years. Her transaction status is 0.0 and she holds 1 product. She has 1 credit card with an average credit type."

Dataset Card for FinBench

Dataset Statistics

We present FinBench, a benchmark for evaluating the performance of machine learning models with both tabular data inputs and profile text inputs.

We first collect hundreds of financial datasets from the Kaggle platform and then screen out ten high-quality datasets for financial risk prediction. The screening criteria is based on the quantity and popularity, column meaningfulness, and the performance of baseline models on those datasets.

FinBench consists of three types of financial risks, i.e., default, fraud, and churn. We process the datasets in a unified data structure and provide an easy-loading API on Model Database.

Task Statistics

The following table reports the task description, dataset name (for datasets loading), the number and positive ratio of train/validation/test sets, the number of classification classes (all is 2), and the number of features.

Task Description Dataset #Classes #Features #Train [Pos%] #Val [Pos%] #Test [Pos%]
Credit-card Default Predict whether a user will default on the credit card or not. cd1 2 9 2738 [7.0%] 305 [6.9%] 1305 [6.2%]
cd2 2 23 18900 [22.3%] 2100 [22.3%] 9000 [21.8%]
Loan Default Predict whether a user will default on the loan or not. ld1 2 12 2118 [8.9%] 236 [8.5%] 1010 [9.0%]
ld2 2 11 18041 [21.7%] 2005 [20.8%] 8592 [21.8%]
ld3 2 35 142060 [21.6%] 15785 [21.3%] 67648 [22.1%]
Credit-card Fraud Predict whether a user will commit fraud or not. cf1 2 19 5352 [0.67%] 595 [1.1%] 2550 [0.90%]
cf2 2 120 5418 [6.0%] 603 [7.3%] 2581 [6.0%]
Customer Churn Predict whether a user will churn or not. (customer attrition) cc1 2 9 4189 [23.5%] 466 [22.7%] 1995 [22.4%]
cc2 2 10 6300 [20.8%] 700 [20.6%] 3000 [19.47%]
cc3 2 21 4437 [26.1%] 493 [24.9%] 2113 [27.8%]

Task #Train #Val #Test
Credit-card Default 21638 2405 10305
Loan Default 162219 18026 77250
Credit-card Fraud 10770 1198 5131
Customer Churn 14926 1659 7108
Total 209553 23288 99794

Data Source

Task Dataset Source
Credit-card Default cd1 Kaggle
cd2 Kaggle
Loan Default ld1 Kaggle
ld2 Kaggle
ld3 Kaggle
Credit-card Fraud cf1 Kaggle
cf2 Kaggle
Customer Churn cc1 Kaggle
cc2 Kaggle
cc3 Kaggle
  • Language: English

Dataset Structure

Data Fields

import datasets

datasets.Features(
    {
        "X_ml": [datasets.Value(dtype="float")],  # (The tabular data array of the current instance)
        "X_ml_unscale": [datasets.Value(dtype="float")],  # (Scaled tabular data array of the current instance)
        "y": datasets.Value(dtype="int64"),  # (The label / ground-truth)
        "num_classes": datasets.Value("int64"),  # (The total number of classes)
        "num_features": datasets.Value("int64"),  # (The total number of features)
        "num_idx": [datasets.Value("int64")],  # (The indices of the numerical datatype columns)
        "cat_idx": [datasets.Value("int64")],  # (The indices of the categorical datatype columns)
        "cat_dim": [datasets.Value("int64")],  # (The dimension of each categorical column)
        "cat_str": [[datasets.Value("string")]],  # (The category names of categorical columns)
        "col_name": [datasets.Value("string")],  # (The name of each column)
        "X_instruction_for_profile": datasets.Value("string"),  # instructions (from tabular data) for profiles
        "X_profile": datasets.Value("string"),  # customer profiles built from instructions via LLMs
    }
)

Data Loading

Model Database Login (Optional)

# OR run Model Database-cli login
from huggingface_hub import login

hf_token = "YOUR_ACCESS_TOKENS"  # https://Model Database.co/settings/tokens
login(token=hf_token)

Loading a Dataset

from datasets import load_dataset

# ds_name_list = ["cd1", "cd2", "ld1", "ld2", "ld3", "cf1", "cf2", "cc1", "cc2", "cc3"]
ds_name = "cd1"  # change the dataset name here
dataset = load_dataset("yuweiyin/FinBench", ds_name)

Loading the Splits

from datasets import load_dataset

ds_name = "cd1"  # change the dataset name here
dataset = load_dataset("yuweiyin/FinBench", ds_name)

train_set = dataset["train"] if "train" in dataset else []
validation_set = dataset["validation"] if "validation" in dataset else []
test_set = dataset["test"] if "test" in dataset else []

Loading the Instances

from datasets import load_dataset

ds_name = "cd1"  # change the dataset name here
dataset = load_dataset("yuweiyin/FinBench", ds_name)
train_set = dataset["train"] if "train" in dataset else []

for train_instance in train_set:
    X_ml = train_instance["X_ml"]  # List[float] (The tabular data array of the current instance)
    X_ml_unscale = train_instance["X_ml_unscale"]  # List[float] (Scaled tabular data array of the current instance)
    y = train_instance["y"]  # int (The label / ground-truth)
    num_classes = train_instance["num_classes"]  # int (The total number of classes)
    num_features = train_instance["num_features"]  # int (The total number of features)
    num_idx = train_instance["num_idx"]  # List[int] (The indices of the numerical datatype columns)
    cat_idx = train_instance["cat_idx"]  # List[int] (The indices of the categorical datatype columns)
    cat_dim = train_instance["cat_dim"]  # List[int] (The dimension of each categorical column)
    cat_str = train_instance["cat_str"]  # List[List[str]] (The category names of categorical columns)
    col_name = train_instance["col_name"]  # List[str] (The name of each column)
    X_instruction_for_profile = train_instance["X_instruction_for_profile"]  # instructions for building profiles
    X_profile = train_instance["X_profile"]  # customer profiles built from instructions via LLMs

Citation

@article{yin2023finbench,
  title   = {FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models},
  author  = {Yin, Yuwei and Yang, Yazheng and Yang, Jian and Liu, Qi},
  journal = {arXiv preprint arXiv:2308.00065},
  year    = {2023},
}
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