MARC details
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
090409a1999 caua b 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
99046067 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781558605527 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1558605525 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(Sirsi) u1356 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
EG-CaNU |
| Transcribing agency |
EG-CaNU |
| Modifying agency |
EG-CaNU |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
ncode |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 |
| Edition number |
21 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Witten, I. H. |
| Fuller form of name |
(Ian H.) |
| 9 (RLIN) |
190 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Data mining : |
| Remainder of title |
practical machine learning tools and techniques with Java implementations / |
| Statement of responsibility, etc. |
Ian H. Witten, Eibe Frank. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
San Francisco, Calif. : |
| Name of publisher, distributor, etc. |
Morgan Kaufmann, |
| Date of publication, distribution, etc. |
2000. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxv, 371 p. ; |
| Dimensions |
24 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references(p. 339-349) and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
The third edition of Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, as well as a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Ch 1 What’s It All About? -- Ch 2 Input: Concepts, Instances, Attributes -- Ch 3 Output: Knowledge Representation -- Ch 4 Algorithms: The Basic Methods -- Ch 5 Credibility: Evaluating What’s Been Learned -- Ch 6 Implementations: Real Machine Learning Schemes -- Ch 7 Data Transformation -- Ch 8 Ensemble Learning -- Ch 9 Moving On: Applications and Beyond -- Ch 10 Introduction to Weka -- Ch 11 The Explorer -- Ch 12 The Knowledge Flow Interface -- Ch 13 The Experimenter -- Ch 14 The Command-Line Interface -- Ch 15 Embedded Machine Learning -- Ch 16 Writing New Learning Schemes -- Ch 17 Tutorial Exercises for the Weka Explorer. |
| 596 ## - |
|---|
| -- |
1 |
| 630 ## - SUBJECT ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Data Mining |
| 9 (RLIN) |
1367 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining |
| 9 (RLIN) |
1368 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Java (Computer program language) |
| 9 (RLIN) |
156 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Frank, Eibe |
| 9 (RLIN) |
1369 |