MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02416nam a2200229Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
NULRC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250520102804.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
250520s9999 xx 000 0 und d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781523321438 |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
NULRC |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA 76.9 .N67 2016 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
North, Matthew |
| Relator term |
author |
| 245 #0 - TITLE STATEMENT |
|---|
| Title |
Data mining for the masses / |
| Statement of responsibility, etc. |
Matthew North |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
SECOND EDITION |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
[Place of publication not identifed] : |
| Name of publisher, distributor, etc. |
CreateSpace Independent Publishing Platform, |
| Date of publication, distribution, etc. |
c2016 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xv, 296 pages : |
| Other physical details |
color illustrations ; |
| Dimensions |
28 cm. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Data mining for the masses /, Data |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Section 1. Data mining basics -- 1. Introduction to data mining and CRISP-DM -- 2. Organizational understanding and data understanding -- 3. Data preparation -- Section 2. Data mining models and methods -- 4. Correlational methods -- 5. Association rules -- 6. k-means clustering -- 7. Discriminant analysis, k-Nearest neighbors and Naive Bayes -- 8. Linear regression -- 9. Logistic regression -- 10. Decision trees -- 11. Neural networks -- 12. Text mining -- Section 3. Special considerations in data mining -- 13. Evaluation and deployment -- 14.Data mining ethics. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
We live in a world that generates tremendous amounts of data—more than ever before. In business, and in our personal lives, we use smartphones and tablets, web sites and watches; with dozens of apps and interfaces to shop, learn, entertain and inform. Businesses increasingly use technology to interact with consumers to provide marketing, customer service, product information and more. All of this technological activity generates data—data that can be useful in many ways. Data mining can help to identify interesting patterns and messages that exist, often hidden beneath the surface. In this modern age of information systems, it is easier than ever before to extract meaning from data. From classification to prediction, data mining can help. In Data Mining for the Masses, Second Edition, professor Matt North—a former risk analyst and software engineer at eBay—uses simple examples and clear explanations with free, powerful software tools to teach you the basics of data mining. In this Second Edition, implementations of these examples are offered in both an updated version of the RapidMiner software, and in the popular R Statistical Package. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
DATA MINING |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Books |
