Professeur Antonio De Braga, Universidade Federal de Minas Gerais, Brazil
Lecture will be taught in English, from June 20th to June 24th from 09:00 to 12:00 at room 5105 ESIEE
- Day 1 : Introduction to Pattern Recognition, principles of Statistical Learning
- Day 2 : Feature Selection and Extraction
- Day 3 : Classifier systems, Bayes Classifier
- Day 4 : Artificial Neural Networks
- Day 5 : Multi-objective learning
Cours aims at giving a general overview of Pattern Recognition systems with emphasis on Artificial Neural Networks and Multi-Objective Learning. Principes of Pattern Recognition and Statistical Learning theory will be given at the beginning of course. Next principles of feature extraction with Principal Component Analysis and Kernel Principal Component Analysis will be presented, which will be followed by the description of feature selection methods, such as Fischer Score and Relief. We will then the discuss the main principles of classifier systems with emphasis on the Bayes Classifier and Artificial Neural Network. Finaly, the principles of Multi-objective learning will be presented in the context of Artificial Neural Network Learning.