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عنوان
Proactive data mining with decision trees /

پدید آورنده
Haim Dahan, Shahar Cohen, Lior Rokach, Oded Maimon

موضوع
Data mining.,Decision trees.,Computer Science.,Data Mining and Knowledge Discovery.,Information Storage and Retrieval.,Information Systems Applications (incl. Internet)

رده
QA76
.
9
.
D343

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
1493905392 (electronic bk.)
(Number (ISBN
9781493905393 (electronic bk.)
Erroneous ISBN
9781493905386

NATIONAL BIBLIOGRAPHY NUMBER

Number
dltt

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Proactive data mining with decision trees /
General Material Designation
[Book]
First Statement of Responsibility
Haim Dahan, Shahar Cohen, Lior Rokach, Oded Maimon

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource (x, 88 pages) :
Other Physical Details
illustrations.

SERIES

Series Title
SpringerBriefs in Electrical and Computer Engineering,
ISSN of Series
2191-8112

INTERNAL BIBLIOGRAPHIES/INDEXES NOTE

Text of Note
Includes bibliographical references

CONTENTS NOTE

Text of Note
Introduction -- Proactive Data Mining: A General Approach -- Proactive Data Mining Using Decision Trees -- Proactive Data Mining in the Real World: Case Studies -- Sensitivity Analysis of Proactive Data Mining -- Conclusions
0

SUMMARY OR ABSTRACT

Text of Note
This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781493905386
International Standard Book Number
9781493905393

TOPICAL NAME USED AS SUBJECT

Data mining.
Decision trees.
Computer Science.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Information Systems Applications (incl. Internet)

(SUBJECT CATEGORY (Provisional

COM-- 000000
COM021030
UNF
UYQE

DEWEY DECIMAL CLASSIFICATION

Number
006
.
312
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
QA76
.
9
.
D343

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Dahan, Haim

CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY

Ohio Library and Information Network.

ORIGINATING SOURCE

Date of Transaction
20201222074526.0
Cataloguing Rules (Descriptive Conventions))
pn

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]
270410

Y

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