Machine Learning and Association rules

Machine Learning and
Association rules
Petr Berka, Jan Rauch
University of Economics, Prague
{berka|rauch}@vse.czTutorial Outline
 Statistics, machine learning and data
mining – basic concepts, similarities and
differences (P. Berka)
 Machine Learning Methods and
Algorithms – general overview and selected
methods (P. Berka)
 Break
 GUHA Method and LISp-Miner System
(J.Rauch)
Tutorial @ COMPSTAT 2010 2Part 1
Statistics, machine learning and
data miningStatistics
 A formal science that deals with collection,
analysis, interpretation, explanation and
presentation of (usually numerical) data.
 The science of making effective use of
numerical data relating to groups of
individuals or experiments
(wikipedia)
Tutorial @ COMPSTAT 2010 4Machine Learning
 „The field of machine learning is concerned
with the question of how to construct computer
programs that automatically improve with
experience.―
(Mitchell, 1997)
 „Things learn when they change their behavior
in a way that makes them perform better in a
future.―
(Witten, Frank, 1999)
Tutorial @ COMPSTAT 2010 5Knowledge Discovery in Databases
 „Non-trivial process of identifying valid, novel,
potentially useful and ultimately understandable
patterns from data.―
(Fayyad et al., 1996)
 „Analysis of observational data sets to find
unsuspected relationships and summarize data in
novel ways that are both understandable ...