
Foundations of Computational Intelligence: Function Approximation and Classification
by Abraham, Ajith; Hassanien, Aboul Ella; Snasel, VaclavRent Textbook
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Summary
Table of Contents
Function Approximation and Classification: Theoretical Foundations | |
Feature Selection for Partial Least Square Based Dimension Reduction | p. 3 |
Classification by the Use of Decomposition of Correlation Integral | p. 39 |
Investigating Neighborhood Graphs for Inducing Density Based Clusters | p. 57 |
Some Issues on Extensions of Information and Dynamic Information Systems | p. 79 |
A Probabilistic Approach to the Evaluation and Combination of Preferences | p. 107 |
Use of the q-Gaussian Function in Radial Basis Function Networks | p. 127 |
Function Approximation and Classification: Success Stories and Real World Applications | |
Novel Biomarkers for Prostate Cancer Revealed by (a,b)-k-Feature Sets | p. 149 |
A Tutorial on Multi-label Classification Techniques | p. 177 |
Computational Intelligence in Biomedical Image Processing | p. 197 |
A Comparative Study of Three Graph Edit Distance Algorithms | p. 223 |
Classification of Complex Molecules | p. 243 |
Intelligent Finite Element Method and Application to Simulation of Behavior of Soils under Cyclic Loading | p. 317 |
An Empirical Evaluation of the Effectiveness of Different Types of Predictor Attributes in Protein Function Prediction | p. 339 |
Genetic Selection Algorithm and Cloning for Data Mining with GMDH Method | p. 359 |
Author Index | p. 377 |
Table of Contents provided by Ingram. All Rights Reserved. |
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