Loan Approval Prediction Machine Learning

Introduction

In this notebook, we are going to predict whether a person is eligible for loan or not. The dataset is from Loan Approval Prediction Hackathon hosted by Analytics Vidhya.

Problem Statement

Dream Housing Finance company deals in all kinds of home loans. They have a presence across all urban, semi-urban and rural areas. The customer first applies for a home loan and after that, the company validates the customer eligiblity for the loan.

The company wants to automate the loan eligibility process (real-time) based on customer detail provided while filling out online application forms. These detials are Gender, Martial status, Education, number of dependents, Income, Loan Amount, Credit history, and others.

This is a Binary Classification problem in which we need to predict our Target label which is Loan Status.

Loan status can have two values: Yes or No.

Yes: if the loan is approved

No: if the loan is disapproved

So using the training dataset we will train our model and try to predict our target column that is Loan Status on the test dataset.

I have used three main Algorithms to predict:

• LogisticRegression
• SVM
• RandomForestClassifier