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عنوان
Feature Selection for Knowledge Discovery and Data Mining

پدید آورنده
by Huan Liu, Hiroshi Motoda.

موضوع
Artificial intelligence.,Computer science.,Data structures (Computer science).

رده

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
9781461376040
(Number (ISBN
9781461556893

NATIONAL BIBLIOGRAPHY NUMBER

Number
b403399

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Feature Selection for Knowledge Discovery and Data Mining
General Material Designation
[Book]
First Statement of Responsibility
by Huan Liu, Hiroshi Motoda.

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Boston, MA :
Name of Publisher, Distributor, etc.
Imprint: Springer,
Date of Publication, Distribution, etc.
1998.

SERIES

Series Title
Springer International Series in Engineering and Computer Science,
Volume Designation
454
ISSN of Series
0893-3405 ;

SUMMARY OR ABSTRACT

Text of Note
With advanced computer technologies and their omnipresent usage, data accumulates in a speed unmatchable by the human's capacity to process data. To meet this growing challenge, the research community of knowledge discovery from databases emerged. The key issue studied by this community is, in layman's terms, to make advantageous use of large stores of data. In order to make raw data useful, it is necessary to represent, process, and extract knowledge for various applications. Feature Selection for Knowledge Discovery and Data Mining offers an overview of the methods developed since the 1970s and provides a general framework in order to examine these methods and categorize them. This book employs simple examples to show the essence of representative feature selection methods and compares them using data sets with combinations of intrinsic properties according to the objective of feature selection. In addition, the book suggests guidelines on how to use different methods under various circumstances and points out new challenges in this exciting area of research. Feature Selection for Knowledge Discovery and Data Mining is intended to be used by researchers in machine learning, data mining, knowledge discovery and databases as a toolbox of relevant tools that help in solving large real-world problems. This book is also intended to serve as a reference book or secondary text for courses on machine learning, data mining, and databases.

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781461376040

PIECE

Title
Springer eBooks

TOPICAL NAME USED AS SUBJECT

Artificial intelligence.
Computer science.
Data structures (Computer science).

PERSONAL NAME - PRIMARY RESPONSIBILITY

Liu, Huan.

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Motoda, Hiroshi.

CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY

SpringerLink (Online service)

ORIGINATING SOURCE

Date of Transaction
20190301081900.0

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

Y

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