Loan Prediction Classification Dataset
A Classification Problem which predicts if a loan will get approved or not
@kaggle.jsonali2003_loan_prediction_classification_dataset
A Classification Problem which predicts if a loan will get approved or not
@kaggle.jsonali2003_loan_prediction_classification_dataset
The dataset contains information about loan applicants and whether their loans were approved. Here's a description of each variable:
Loan_ID: Unique identifier for each loan application.
Gender: Gender of the applicant (Male, Female).
Married: Marital status of the applicant (Yes, No).
Dependents: Number of dependents the applicant has.
Education: Education level of the applicant (Graduate, Under Graduate).
Self_Employed: Whether the applicant is self-employed or not (Yes, No).
ApplicantIncome: Income of the applicant.
CoapplicantIncome: Income of the co-applicant.
LoanAmount: Loan amount applied for (in thousands).
Loan_Amount_Term: Term of the loan in months.
Credit_History: Whether the applicant's credit history meets guidelines (1 = Yes, 0 = No).
Property_Area: Area where the applicant's property is located (Urban, Semi Urban, Rural).
Loan_Status: Whether the loan was approved or not (Y = Yes, N = No).
CREATE TABLE output (
"loan_id" VARCHAR,
"loan_status" BIGINT
);CREATE TABLE test (
"loan_id" VARCHAR,
"gender" VARCHAR,
"married" VARCHAR,
"dependents" VARCHAR,
"education" VARCHAR,
"self_employed" VARCHAR,
"applicantincome" BIGINT,
"coapplicantincome" BIGINT,
"loanamount" DOUBLE,
"loan_amount_term" DOUBLE,
"credit_history" DOUBLE,
"property_area" VARCHAR
);CREATE TABLE train (
"loan_id" VARCHAR,
"gender" VARCHAR,
"married" VARCHAR,
"dependents" VARCHAR,
"education" VARCHAR,
"self_employed" VARCHAR,
"applicantincome" BIGINT,
"coapplicantincome" DOUBLE,
"loanamount" DOUBLE,
"loan_amount_term" DOUBLE,
"credit_history" DOUBLE,
"property_area" VARCHAR,
"loan_status" VARCHAR
);Anyone who has the link will be able to view this.