Analytical Learning. Lehrstuhl für Informatik 2 Gabriella Kókai: Maschine Learning Content Introduction Difference between Inductive and Analytical Learning.
1 Concept Learning and the General-to-Specific Ordering.
PAC Learning 8/5/2005. purpose Effort to understand negative selection algorithm from totally different aspects –Statistics –Machine learning What is.
Bayesian models of inductive learning Josh Tenenbaum & Tom Griffiths MIT Computational Cognitive Science Group Department of Brain and Cognitive Sciences.
Machine Learning: Introduction to Neural Networks
Homework 3: Naive Bayes Classification. Bayesian Networks Reading assignment: S. Wooldridge, Bayesian Belief Networks (linked from course webpage)
CS 478 - Inductive Bias1 Inductive Bias: How to generalize on novel data.
Statistical Learning Chapter 20 of AIMA KAIST CS570 Lecture note Based on AIMA slides, Jahwan Kim’s slides and Duda, Hart & Stork’s slides.
CS 188: Artificial Intelligence Learning III: Statistical learning Instructor: Stuart Russell--- University of California, Berkeley.
Università di Milano-Bicocca Laurea Magistrale in Informatica Corso di APPRENDIMENTO E APPROSSIMAZIONE Prof. Giancarlo Mauri Lezione 2 - Concept Learning.
1 Classification and regression trees Pierre Geurts Stochastic methods (Prof. L.Wehenkel) University of Liège.
CS-424 Gregory Dudek Lecture 14 Learning –Probably approximately correct learning (cont’d) –Version spaces –Decision trees.
