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عنوان
Principles of Data Mining /

پدید آورنده
by Max Bramer.

موضوع
Artificial intelligence.,Computer programming.,Computer science.,Database management.,Information storage and retrieval.,Artificial intelligence.,Computer programming.,Computer science.,Database management.

رده
QA75
.
5-76
.
95

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
1447173066
(Number (ISBN
1447173074
(Number (ISBN
9781447173069
(Number (ISBN
9781447173076
Erroneous ISBN
9781447173069

NATIONAL BIBLIOGRAPHY NUMBER

Number
b623631

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Principles of Data Mining /
General Material Designation
[Book]
First Statement of Responsibility
by Max Bramer.

EDITION STATEMENT

Edition Statement
3rd ed. 2016.

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource (XV, 526 pages 123 illustrations) :
Other Physical Details
online resource

SERIES

Series Title
Undergraduate Topics in Computer Science,
ISSN of Series
1863-7310

CONTENTS NOTE

Text of Note
Introduction to Data Mining -- Data for Data Mining -- Introduction to Classification: Naïve Bayes and Nearest Neighbour -- Using Decision Trees for Classification -- Decision Tree Induction: Using Entropy for Attribute Selection -- Decision Tree Induction: Using Frequency Tables for Attribute Selection -- Estimating the Predictive Accuracy of a Classifier -- Continuous Attributes -- Avoiding Overfitting of Decision Trees -- More About Entropy -- Inducing Modular Rules for Classification -- Measuring the Performance of a Classifier -- Dealing with Large Volumes of Data -- Ensemble Classification -- Comparing Classifiers -- Associate Rule Mining I -- Associate Rule Mining II -- Associate Rule Mining III -- Clustering -- Mining -- Classifying Streaming Data -- Classifying Streaming Data II: Time-dependent Data -- Appendix A -- Essential Mathematics -- Appendix B -- Datasets -- Appendix C -- Sources of Further Information -- Appendix D -- Glossary and Notation -- Appendix E -- Solutions to Self-assessment Exercises -- Index.
0

SUMMARY OR ABSTRACT

Text of Note
This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.

OTHER EDITION IN ANOTHER MEDIUM

International Standard Book Number
9781447173069

TOPICAL NAME USED AS SUBJECT

Artificial intelligence.
Computer programming.
Computer science.
Database management.
Information storage and retrieval.
Artificial intelligence.
Computer programming.
Computer science.
Database management.

(SUBJECT CATEGORY (Provisional

COM030000
UND
UNH

DEWEY DECIMAL CLASSIFICATION

Number
025
.
04
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
QA75
.
5-76
.
95

PERSONAL NAME - PRIMARY RESPONSIBILITY

Bramer, Max

ORIGINATING SOURCE

Date of Transaction
20200617082729.0
Cataloguing Rules (Descriptive Conventions))
pn

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

Y

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