- Knowing and understanding of the basic problems terms and methods of classification and regression methods (k1,k2)
- Knowing and understanding of the basic problems terms and methods of boosting, bagging and random forests (k1,k2)
- Applying classification and regression methods with the freeware R (k3)
- Understanding and applying simple unsupervised learning techniques (k2, k3)
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- Classification methods
- Discriminant analysis
- Regression trees
- Boosting
- Bagging and random forests
- Neural networks
- Principle components methods
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