ENGLISH

Metalearning: Applications to Data Mining

By Pavel Brazdil , Christophe Giraud-Carrier , Carlos Soares , Ricardo Vilalta (auth.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2009
ISBN
3540732624, 9783540732624
DOI
10.1007/978-3-540-73263-1
LCC
Q325.5 .M38 2009
Open Library ID
OL24561221M
Language
english
Format
PDF
Filesize
5 MB (5409191 bytes)
Series
Cognitive Technologies
Edition
1
Pages
176\182
Topic
Education
Time added
2011-06-04 13:46:07
Artificial Intelligence (incl. Robotics); Data Min

Description

Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

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