Skip to content

A predictive model that uses several machine learning algorithms to predict the eligibility of loan applicants based on several factors

Notifications You must be signed in to change notification settings

joymnyaga/CreditAnalytics-Loan-Prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 

Repository files navigation

Credit-Analysis (Machine-Learning)

The following project aims to predict the eligibility of loan applicants for credit using several machine learning algorithms. The algorithms are assessed based on their accuracy score to select the best algorithm for building a predictive model

Algorithms Used a) Logistic Regression b) Decision Tree c) Random Forest d) Support Vector Machine e) Naive Bayes f) k - Nearest Neighbors g) Gradient Boosting Machine

Data Attributes 1.Loan_ID 2.Gender 3.Married 4.Dependents 5.Education 6.Self_Employed 7.ApplicantIncome 8.CoApplicantIncome 9.Loan_Amount 10.Loan_Amount_Term 11.Credit_History 12.Property Area 13.Loan_Status

Releases

No releases published

Packages

No packages published

Languages