Advances in Feature Selection for Data and Pattern Recognition

• Corporate Author: SpringerLink (Online service)
• Other Authors: Stańczyk, Urszula (Editor, http://id.loc.gov/vocabulary/relators/edt), Zielosko, Beata (Editor, http://id.loc.gov/vocabulary/relators/edt), Jain, Lakhmi C. (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Intelligent Systems Reference Library, 138
• Subjects: Computational intelligence.; Artificial intelligence.; Pattern recognition.; Data mining.; Computational Intelligence.; Artificial Intelligence.; Pattern Recognition.; Data Mining and Knowledge Discovery.

This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some...

Table of Contents:

• An Introduction
• Attribute Selection Based on Reduction of Numerical Attribute During Discretization
• Improving Bagging Ensembles for Class Imbalanced Data by Active Learning
• Optimization of Decision Rules Relative to Length Based on Modified Dynamic Programming Approach
• Ranking-Based Rule Classifier Optimisation
• Attribute Selection in a Dispersed Decision-Making System
• Feature Selection Approach for Rule-based Knowledge Bases
• Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data.