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Train a Neural Network to Classify Loan Applications using Decision Trees

In this project, we are going to work on a German credit dataset project using classification techniques like Decision Tree, Neural Networks etc to Classify Loan Applications using R.
What are the prerequisites for this project?
  • R-Studio
  • Language used: R

What will you learn

  • Application of Logistic Regression
  • Decision Tree based rules
  • Neural Network
  • Benchmarking
  • Feature selection
  • Feature Engineering

Project Description

The German credit dataset contains information on 1000 loan applicants. Each applicant is described by a set of 20 different attributes. Of these 20 attributes, seventeen attributes are discrete while three are continuous. The main idea is to use techniques from the field of information theory to select a set of important attributes that can be used to classify tuples. A neural network is trained using these attributes; the neural network is then used to classify tuples.



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