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https://github.com/decodedco/translators-r


https://github.com/decodedco/translators-r

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README

          

# translators-R

## Introduction

We want to analyse loans in order to predict likelihood of Default.

To do this, we will experiment with:
* Decision trees
* Random forests
* Neural networks

Each of these models relies on us pre-defining some input parameters.
We must assess how well these models perform (depending on the input parameters), in order to find the one that best predicts Default.

The data, and a starting R script for our analysis can be found here.

You must create a copy of the template notebook, and use your copy to try out the methods.

## R notebooks

Notebooks are a great way for organising text and code in order to follow through data exploration and analysis.

You can preview the analysis that we will carry out here in `Analysis_Template.ipynb`.