Advances in Feature Selection for Data and Pattern Recognition

✍ Scribed by Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain (eds.)

• Publisher: Springer International Publishing
• Year: 2018
• Tongue: English
• Leaves: 334
• Series: Intelligent Systems Reference Library 138
• Edition: 1
• Category: Library

✦ Synopsis

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 of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved.
Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.

✦ Table of Contents

Front Matter ....Pages i-xviii
Advances in Feature Selection for Data and Pattern Recognition: An Introduction (Urszula Stańczyk, Beata Zielosko, Lakhmi C. Jain)....Pages 1-9
Front Matter ....Pages 11-11
Attribute Selection Based on Reduction of Numerical Attributes During Discretization (Jerzy W. Grzymała-Busse, Teresa Mroczek)....Pages 13-24
Improving Bagging Ensembles for Class Imbalanced Data by Active Learning (Jerzy Błaszczyński, Jerzy Stefanowski)....Pages 25-52
Attribute-Based Decision Graphs and Their Roles in Machine Learning Related Tasks (João Roberto Bertini Junior, Maria do Carmo Nicoletti)....Pages 53-71
Optimization of Decision Rules Relative to Length Based on Modified Dynamic Programming Approach (Beata Zielosko, Krzysztof Żabiński)....Pages 73-93
Front Matter ....Pages 95-95
Generational Feature Elimination and Some Other Ranking Feature Selection Methods (Wiesław Paja, Krzysztof Pancerz, Piotr Grochowalski)....Pages 97-112
Ranking-Based Rule Classifier Optimisation (Urszula Stańczyk)....Pages 113-131
Attribute Selection in a Dispersed Decision-Making System (Małgorzata Przybyła-Kasperek)....Pages 133-162
Feature Selection Approach for Rule-Based Knowledge Bases (Agnieszka Nowak-Brzezińska)....Pages 163-182
Front Matter ....Pages 183-183
Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data (Annamária Szenkovits, Regina Meszlényi, Krisztian Buza, Noémi Gaskó, Rodica Ioana Lung, Mihai Suciu)....Pages 185-202
Shape Descriptions and Classes of Shapes. A Proximal Physical Geometry Approach (James Francis Peters, Sheela Ramanna)....Pages 203-225
Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion (Piotr Szczuko, Michał Lech, Andrzej Czyżewski)....Pages 227-239
Application of Tolerance Near Sets to Audio Signal Classification (Ashmeet Singh, Sheela Ramanna)....Pages 241-266
Front Matter ....Pages 267-267
Visual Analysis of Relevant Features in Customer Loyalty Improvement Recommendation (Katarzyna A. Tarnowska, Zbigniew W. Raś, Lynn Daniel, Doug Fowler)....Pages 269-293
Evolutionary and Aggressive Sampling for Pattern Revelation and Precognition in Building Energy Managing System with Nature-Based Methods for Energy Optimization (Jarosław Utracki, Mariusz Boryczka)....Pages 295-319
Back Matter ....Pages 321-328

✦ Subjects

Computational Intelligence