Objective: Binary-Classification

Assignment from Arya.ai

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Files

• EDA
• Predictions of Test Data
• Print Performance of Models
• Requirements.txt

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Train Dataset Shape -> (3909,58)
Train Dataset Shape -> (690,58)

Dataset: Sparse and High Dimensional

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Key Steps:

1. Used RandomForest Classifier for feature selection.
2. Selected top 30 features with respect to their feature importance.
3. For metric I have considered Binary CrossEntropy and AUC score.
4. The best model I get is Xgboost.