LoanEligibilty_ML

Analysis of Streaming dataset with different attributes of a Customer to find whether they are eligible for a loan.

This analysis is from data presented in Kaggle: Loan Eligibility Prediction

This project analyses a streaming dataset of Customers. The Machine Learning algorithm then decides if they are eligible for a loan or not. Classification algorithms applied include:

• No-change Classifier
• Majority Class Classifier
• Hoeffding Trees
• SAM-KNN
• Hoeffding Adaptive Trees(HAT)
• Adaptive Random Forest(ARF)
• Leverage bagging

The accuracies of the above algorithms on the dataset is shown below

As expected the No-change classifier being very basic one delivers poor performance. The HAT delivers the best performance on this dataset