Decision Support Systems
Present algorithms that can be used for extracting knowledge from datasets. In particular, the course will cover the case of supervised learning.
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
Machine Learning, Tom Mitchell, McGraw Hill, 1997.
Papers and materials provided by the professor.
Theoretical classes where the different techniques commonly used for taking profitable decisions are presented
First epoch: two tests. The final grade is he average of the two tests. A minimum grade is required in both the two tests.
Second epoch: final written exam.
Optimization problems: definitions and examples.
No free lunch theorem
Local search techniques
Population-based optimization algorithms
Bio-inspired machine learning techniques
Supervised and unsupervised learning
Multi criteria optimization and Pareto dominance
Programs where the course is taught: