Meta-Learning in Computational Intelligence
Editors: Jankowski, Norbert, Duch, Włodzisław, Grąbczewski, Krzysztof (Eds.)
Free Preview- Recent research in Meta-learning in computational intelligence
- Presents new Developments and Trends in Computational Intelligence and Learning
- Written by leading experts in the field
Buy this book
- About this book
-
Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open.
Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process.This is where algorithms that learn how to learnl come to rescue.
Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn.This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
- Table of contents (10 chapters)
-
-
Universal Meta-Learning Architecture and Algorithms
Pages 1-76
-
Meta-Learning of Instance Selection for Data Summarization
Pages 77-95
-
Choosing the Metric: A Simple Model Approach
Pages 97-115
-
Meta-Learning Architectures: Collecting, Organizing and Exploiting Meta-Knowledge
Pages 117-155
-
Computational Intelligence for Meta-Learning: A Promising Avenue of Research
Pages 157-177
-
Table of contents (10 chapters)
Recommended for you
Bibliographic Information
- Bibliographic Information
-
- Book Title
- Meta-Learning in Computational Intelligence
- Editors
-
- Norbert Jankowski
- Włodzisław Duch
- Krzysztof Grąbczewski
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 358
- Copyright
- 2011
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer Berlin Heidelberg
- eBook ISBN
- 978-3-642-20980-2
- DOI
- 10.1007/978-3-642-20980-2
- Hardcover ISBN
- 978-3-642-20979-6
- Softcover ISBN
- 978-3-642-26858-8
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- IX, 359
- Topics
