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Loan-Case-will-be-Paid-OFF-or-NOT-Prediction-using-Classification-with-Python

In this project, you will complete a notebook where you will build a classifier to predict whether a loan case will be paid off or not.

You load a historical dataset from previous loan applications, clean the data, and apply different classification algorithm on the data. You are expected to use the following algorithms to build your models:

  • k-Nearest Neighbour

  • Decision Tree

  • Support Vector Machine

  • Logistic Regression

The results is reported as the accuracy of each classifier, using the following metrics when these are applicable:

  • Jaccard index

  • F1-score

  • LogLoass

This dataset is about past loans. The Loan_train.csv data set includes details of 346 customers whose loan are already paid off or defaulted. It includes following fields:

Field Description
Loan_status Whether a loan is paid off on in collection
Principal Basic principal loan amount at the
Terms Origination terms which can be weekly (7 days), biweekly, and monthly payoff schedule
Effective_date When the loan got originated and took effects
Due_date Since it’s one-time payoff schedule, each loan has one single due date
Age Age of applicant
Education Education of applicant
Gender The gender of applicant