Feature Selection for Data and Pattern Recognition [electronic resource] /
edited by Urszula Stańczyk, Lakhmi C. Jain.
- XVIII, 355 p. 74 illus., 20 illus. in color. online resource.
- Studies in Computational Intelligence, 584 1860-949X ; .
- Studies in Computational Intelligence, 584 .
Feature Selection for Data and Pattern Recogniton: an Introduction -- Part I Estimation of Feature Importance -- Part II Rough Set Approach to Attribute Reduction -- Part III Rule Discovery and Evaluation -- Part IV Data- and Domain-oriented Methodologies.
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.
9783662456200
10.1007/978-3-662-45620-0 doi
Engineering.
Artificial intelligence.
Computational intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Q342
006.3
Feature Selection for Data and Pattern Recogniton: an Introduction -- Part I Estimation of Feature Importance -- Part II Rough Set Approach to Attribute Reduction -- Part III Rule Discovery and Evaluation -- Part IV Data- and Domain-oriented Methodologies.
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.
9783662456200
10.1007/978-3-662-45620-0 doi
Engineering.
Artificial intelligence.
Computational intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Q342
006.3