The goal of this model is to predict if a loan will get approved or not.
In this project , we need to predict the target variable Loan_Status which has 2 values Y and N: Below are the Variable Descriptions : Loan_ID - Unique Loan ID Gender - Male/ Female Married - Applicant married (Y/N) Dependents - Number of dependents Education - Applicant Education (Graduate/ Under Graduate) Self_Employed - Self employed (Y/N) ApplicantIncome - Applicant income CoapplicantIncome - Coapplicant income LoanAmount - Loan amount in thousands Loan_Amount_Term - Term of loan in months Credit_History - credit history meets guidelines Property_Area - Urban/ Semi Urban/ Rural Loan_Status - Loan approved (Y/N) - We have replaced the missing values in the data with the Mode of the columns i.e. The most frequent value in the data. - Also we have normalized the data so that the different features take on similar ranges of values so that gradient descents can converge more quickly. - We have used the Two class Logistic Regression model and have the below results: Accuracy - 0.799 Precision - 0.766 Recall - 0.975