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Feature Extraction, Construction and Selection

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Cover of 'Feature Extraction, Construction and Selection'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Less Is More
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    Chapter 2 Feature Weighting for Lazy Learning Algorithms
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    Chapter 3 The Wrapper Approach
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    Chapter 4 Data-Driven Constructive Induction: Methodology and Applications
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    Chapter 5 Selecting Features by Vertical Compactness of Data
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    Chapter 6 Relevance Approach to Feature Subset Selection
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    Chapter 7 Novel Methods for Feature Subset Selection with Respect to Problem Knowledge
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    Chapter 8 Feature Subset Selection Using a Genetic Algorithm
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    Chapter 9 A Relevancy Filter for Constructive Induction
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    Chapter 10 Lexical Contextual Relations for the Unsupervised Discovery of Texts Features
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    Chapter 11 Integrated Feature Extraction Using Adaptive Wavelets
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    Chapter 12 Feature extraction via Neural networks
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    Chapter 13 Using Lattice-Based Framework as a Tool for Feature Extraction
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    Chapter 14 Constructive Function Approximation
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    Chapter 15 A Comparison of Constructing Different Types of New Feature For Decision Tree Learning
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    Chapter 16 Constructive Induction: Covering Attribute Spectrum
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    Chapter 17 Feature Construction Using Fragmentary Knowledge
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    Chapter 18 Constructive Induction on Continuous Spaces
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    Chapter 19 Evolutionary Feature Space Transformation
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    Chapter 20 Feature Transformation By Function Decomposition
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    Chapter 21 Constructive Induction of Cartesian Product Attributes
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    Chapter 22 Towards Automatic Fractal Feature Extraction For Image Recognition
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    Chapter 23 Feature Transformation Strategies for a Robot Learning Problem
  25. Altmetric Badge
    Chapter 24 Interactive Genetic Algorithm Based Feature Selection and Its Application to Marketing Data Analysis
Attention for Chapter 23: Feature Transformation Strategies for a Robot Learning Problem
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Chapter title
Feature Transformation Strategies for a Robot Learning Problem
Chapter number 23
Book title
Feature Extraction, Construction and Selection
Published by
Springer, Boston, MA, January 1998
DOI 10.1007/978-1-4615-5725-8_23
Book ISBNs
978-1-4613-7622-4, 978-1-4615-5725-8
Authors

Luis Seabra Lopes, Luis M. Camarinha-Matos, Lopes, Luis Seabra, Camarinha-Matos, Luis M.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 29%
Professor 1 7%
Student > Doctoral Student 1 7%
Student > Ph. D. Student 1 7%
Unknown 7 50%
Readers by discipline Count As %
Engineering 6 43%
Computer Science 1 7%
Unknown 7 50%