Loan Prediction using Machine Learning

This project aims to develop a predictive model for determining the approval status of loans. The model will utilize machine learning techniques to analyze various features and make accurate predictions regarding whether a loan application should be approved or not.

• The machine learning algorithms used in this project are -
  • Logistic Regression
  • Decision Tree
  • Naive Bayes
  • Random Forest
  • K-Nearest neighbors
  • Linear Discriminant Analysis
  • Support Vector Machine

Dataset

• The dataset used for this project is collected from Kaggle at https://www.kaggle.com/datasets/altruistdelhite04/loan-prediction-problem-dataset
• The dataset consists of two .csv files that are :
  • Training Data - It is labeled data of 614 rows i.e, consists of features as well as targets.
  • Testing Data - It consists of only features on which predictions need to be generated.