This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition.
Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks.
This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.
| ISBN: | 9783662456194 |
| Publication date: | 15th January 2015 |
| Author: | Urszula StaÔnczyk, L C Jain |
| Publisher: | Springer an imprint of Springer Berlin Heidelberg |
| Format: | Hardback |
| Pagination: | 355 pages |
| Series: | Studies in Computational Intelligence |
| Genres: |
Artificial intelligence |
This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks.
Feature Selection for Data and Pattern Recognition features in the following genres: Artificial intelligence
Hardback. Not Available.
Feature Selection for Data and Pattern Recognition was written by Urszula StaÔnczyk, L C Jain and published by Springer an imprint of Springer Berlin Heidelberg
Feature Selection for Data and Pattern Recognition has 355 pages
Yes it is part of Studies in Computational Intelligence series