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Prediction of Non-acceptance of University Offer

Goal of this ML project is to predict applicants who do not accept after being offered a place to study at various partner universities at the undergraduate level.

This project uses real organizational data and thus some parts have been excluded, such as EDA, checking data values, etc. Results such as Confustion Matrix shows percentages instead.

Results

Several models were tested and tuned. The best model was a Random Forest with the following metrics:

  • AUC: 0.90
  • Accuracy: 0.927
  • Precision 0.968
  • Recall: 0.736

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RandomForest predicting student acceptance of Uni offer.

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