Data Mining Project

This notebook is the final project for data-mining course. For this project we applied data-mining techniques with python's scikit-learn library. The project consist:

1. Data Exploration:
   • statistics about the features
   • scatter plots for the features
   • correlation matrix
   • violinplot
2. Feature Engineering:
   • LDA
   • PCA
   • Modification for PCA
   • Feature Generation
3. KNN
   • Hyperparameter optimization
   • apply with different preprocessing
4. Gaussian Naive Bayes
   • apply with different preprocessing
5. Multilayer Perceptron:
   • apply with different preprocessing
6. Boosting:
   • Based on decision trees
   • Based on Gaussian Naive Bayes
7. Evaluation:
   • Confusion matrix
   • Receiver operating characteristic (ROC)