000 -LEADER |
fixed length control field |
04982nam a22005175i 4500 |
001 - CONTROL NUMBER |
control field |
978-3-540-33019-6 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20161121231118.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
100301s2006 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783540330196 |
-- |
978-3-540-33019-6 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/3-540-33019-4 |
Source of number or code |
doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA329-348 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA640-643 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
TBJ |
Source |
bicssc |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
MAT003000 |
Source |
bisacsh |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
519 |
Edition number |
23 |
245 10 - TITLE STATEMENT |
Title |
Multi-Objective Machine Learning |
Medium |
[electronic resource] / |
Statement of responsibility, etc. |
edited by Yaochu Jin. |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
Berlin, Heidelberg : |
Name of producer, publisher, distributor, manufacturer |
Springer Berlin Heidelberg, |
Date of production, publication, distribution, manufacture, or copyright notice |
2006. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
XIV, 660 p. 254 illus. |
Other physical details |
online resource. |
336 ## - CONTENT TYPE |
Content type term |
text |
Content type code |
txt |
Source |
rdacontent |
337 ## - MEDIA TYPE |
Media type term |
computer |
Media type code |
c |
Source |
rdamedia |
338 ## - CARRIER TYPE |
Carrier type term |
online resource |
Carrier type code |
cr |
Source |
rdacarrier |
347 ## - DIGITAL FILE CHARACTERISTICS |
File type |
text file |
Encoding format |
PDF |
Source |
rda |
490 1# - SERIES STATEMENT |
Series statement |
Studies in Computational Intelligence, |
International Standard Serial Number |
1860-949X ; |
Volume/sequential designation |
16 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Multi-Objective Clustering, Feature Extraction and Feature Selection -- Feature Selection Using Rough Sets -- Multi-Objective Clustering and Cluster Validation -- Feature Selection for Ensembles Using the Multi-Objective Optimization Approach -- Feature Extraction Using Multi-Objective Genetic Programming -- Multi-Objective Learning for Accuracy Improvement -- Regression Error Characteristic Optimisation of Non-Linear Models -- Regularization for Parameter Identification Using Multi-Objective Optimization -- Multi-Objective Algorithms for Neural Networks Learning -- Generating Support Vector Machines Using Multi-Objective Optimization and Goal Programming -- Multi-Objective Optimization of Support Vector Machines -- Multi-Objective Evolutionary Algorithm for Radial Basis Function Neural Network Design -- Minimizing Structural Risk on Decision Tree Classification -- Multi-objective Learning Classifier Systems -- Multi-Objective Learning for Interpretability Improvement -- Simultaneous Generation of Accurate and Interpretable Neural Network Classifiers -- GA-Based Pareto Optimization for Rule Extraction from Neural Networks -- Agent Based Multi-Objective Approach to Generating Interpretable Fuzzy Systems -- Multi-objective Evolutionary Algorithm for Temporal Linguistic Rule Extraction -- Multiple Objective Learning for Constructing Interpretable Takagi-Sugeno Fuzzy Model -- Multi-Objective Ensemble Generation -- Pareto-Optimal Approaches to Neuro-Ensemble Learning -- Trade-Off Between Diversity and Accuracy in Ensemble Generation -- Cooperative Coevolution of Neural Networks and Ensembles of Neural Networks -- Multi-Objective Structure Selection for RBF Networks and Its Application to Nonlinear System Identification -- Fuzzy Ensemble Design through Multi-Objective Fuzzy Rule Selection -- Applications of Multi-Objective Machine Learning -- Multi-Objective Optimisation for Receiver Operating Characteristic Analysis -- Multi-Objective Design of Neuro-Fuzzy Controllers for Robot Behavior Coordination -- Fuzzy Tuning for the Docking Maneuver Controller of an Automated Guided Vehicle -- A Multi-Objective Genetic Algorithm for Learning Linguistic Persistent Queries in Text Retrieval Environments -- Multi-Objective Neural Network Optimization for Visual Object Detection. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Engineering. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Statistical physics. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Dynamical systems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Applied mathematics. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Engineering mathematics. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Appl.Mathematics/Computational Methods of Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Artificial Intelligence (incl. Robotics). |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Statistical Physics, Dynamical Systems and Complexity. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Jin, Yaochu. |
Relator term |
editor. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Relationship information |
Printed edition: |
International Standard Book Number |
9783540306764 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
Uniform title |
Studies in Computational Intelligence, |
International Standard Serial Number |
1860-949X ; |
Volume/sequential designation |
16 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
http://dx.doi.org/10.1007/3-540-33019-4 |
912 ## - |
-- |
ZDB-2-ENG |