Lectures in english
- Lecture 1: Introduction
- Lecture 2: Classification problem and evaluation methods
- Lecture 3: Decision tree
- Lecture 4: Boolean reasoning and rough set theory
- Lecture 5: Redukty i reguły decyzyjne
- Lecture 6: Neural networks and backpropagation algorithm
- Lecture 7: Support Vector Machine (SVM)
- Lecture 8: Statistical Learning Theory: PAC learning model
- Lecture 9: Statistical Learning Theory: Vapnik-Chervonenkis dimension
- Lecture 10: Ensample Learning: Bootstrap, Bagging, Boosting, Stacking
- Lecture 11: Hidden Markov Model
- Lecture 12: Fuzzy sets and fuzzy decision making
- Lecture 13: Clustering
Pass examination paper: DSS - EXAMINATION in 2018