/Loan-Approval-Prediction

Assessing different models to predict whether a loan will be approved.

Primary LanguageJupyter Notebook

Loan-Approval-Prediction

Problem Statement

The aim of the project is to experiment, design and implement a loan prediction system using the given dataset to automate the loan eligibility process based on customer details provided such as:

  • Gender
  • Marital Status
  • Number of dependents
  • Education level
  • Self employment status
  • Credit history
  • Property area
  • Income level

Algorithms Used

The following machine learning algorithms are used for the given problem statement:

Logistic Regression

Logisitic Regression is a kind of supervised learning algorithm used for predicting the categorical dependent variable using a given set of independent variables. The accuracy achieved is 80.58%.

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XGBoost

XGBoost is a decision-tree-based ensemble Machine Learning algorithm that uses a gradient boosting framework. The accuracy achieved is 80.58%.

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