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Metalearning Applications to Data Mining /
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,...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2009.
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| Edición: | 1st ed. 2009. |
| Colección: | Cognitive Technologies,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-540-73263-1 | ||
| 003 | DE-He213 | ||
| 005 | 20220116034259.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100301s2009 gw | s |||| 0|eng d | ||
| 020 | |a 9783540732631 |9 978-3-540-73263-1 | ||
| 024 | 7 | |a 10.1007/978-3-540-73263-1 |2 doi | |
| 050 | 4 | |a Q334-342 | |
| 050 | 4 | |a TA347.A78 | |
| 072 | 7 | |a UYQ |2 bicssc | |
| 072 | 7 | |a COM004000 |2 bisacsh | |
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| 100 | 1 | |a Brazdil, Pavel. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Metalearning |h [electronic resource] : |b Applications to Data Mining / |c by Pavel Brazdil, Christophe Giraud Carrier, Carlos Soares, Ricardo Vilalta. |
| 250 | |a 1st ed. 2009. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2009. | |
| 300 | |a XI, 176 p. 53 illus. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Cognitive Technologies, |x 2197-6635 | |
| 505 | 0 | |a Metalearning: Concepts and Systems -- Metalearning for Algorithm Recommendation: an Introduction -- Development of Metalearning Systems for Algorithm Recommendation -- Extending Metalearning to Data Mining and KDD -- Extending Metalearning to Data Mining and KDD -- Bias Management in Time-Changing Data Streams -- Transfer of Metaknowledge Across Tasks -- Composition of Complex Systems: Role of Domain-Specific Metaknowledge. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Automated Pattern Recognition. |
| 700 | 1 | |a Giraud Carrier, Christophe. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Soares, Carlos. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Vilalta, Ricardo. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783642092312 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540868064 |
| 776 | 0 | 8 | |i Printed edition: |z 9783540732624 |
| 830 | 0 | |a Cognitive Technologies, |x 2197-6635 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-540-73263-1 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||