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Finding-Donors-for-CharityML

This project contains an ipython jupyter notebook of my jupyter project part of my udacity nanodegree. I have selected and trained a model for predicting the salary of individuals given many features This was a binary classification problem The outcome was is the salary of individual is <=50K or >50K

Model Used

I have tried three classification models

  1. SVM
  2. Gaussian Bayes Theoram
  3. AdaBoost Classifier

The best one was AdaBoost as it had highest accurancy and F-score.

Conclusion

It could be helpful to send the application of donation only to those customers who earn more than 50K. This have a better probabiltiy of donating.

References

The dataset for this project originates from the UCI Machine Learning Repository. The datset was donated by Ron Kohavi and Barry Becker, which you can find here