Classification
Comprehensive application of ML algorithms in classification problem under caret (R) and scikit-learn (Python) frameworks
- Boosting
- Adaboost, GBM, XGboost
- Bagging
- Random forest
- Decision tree
- CART, Conditional inference tree
- Discriminant analysis
- LDA, QDA
- Generalized linear regression
- K-nearest neighbors
- Naive Bayes
- Neural networks
- Regularization
- LASSO (L1), Ridge(L2), Elastic net
- Support vector machines
Data Source
Red wine quality dataset from UCI Machine Learning Repository