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Predictive model to identify top 20 donors for a national veteran’s organization.

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Predicting Donors - KDD Cup 1998 Data

Problem Statement - Predict if the previous donors of a national veteran organization are going to donate again.

Data Source

Installation

Download the data

  • Clone this repo to your computer.
  • Get into the folder using cd PredictingDonors.
  • Download the data file 'cup98lrn.zip' from the data source mentioned above
  • Extract the text file from the zip folder and open it in excel.
  • Save the file as 'cup98lrn.csv' (comma delimeted csv file format).
  • Remove all the zip files by running rm *.zip.

Install the requirements

  • Make sure you use Python 3.
  • Install all the required libraries. (or choose an easy life and use Anaconda :D )

Usage

  • Run python Donors.py.
    • This will run 4 predictive models, and print performance of each model measured in 4 metrics
      • Recall
      • F1
      • Precision
      • Accuracy

Extending this

If you want to extend this work, here are a few places to start:

  • Run regression on the scored dataset generated from 'Donors.py' and estimate return from direct mailing to maximise donation profits.

Current Result

result image

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Predictive model to identify top 20 donors for a national veteran’s organization.

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