- Participated in a kaggle competition to predict popularity of songs given song features
- Digged a lot on how to deal with outliers and ML algorithms sensitive to outliers
- Learned many more techniques to deal Imbalanced data
- Link to the notebook
- Practiced on a Kaggle Data to predict whether student get admission
- The Results are:
Logistic Regression:
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Accuracy of Logistic Regression is 0.475
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Accuracy of Logistic Regression is 59.5
Support Vector Machine
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Accuracy of Support Vector Machine is 0.65
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Accuracy of Support Vector Machine is 50.0
Notes: Here I have not removed the outliers(Need to remove it and train again) Used Label Encoder to handle categorical data(Can use better encoding techniques) Used simple classifiers - Logistic Regression and Support Vector Machine