Just Enough R! : (Record no. 74762)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04407cam a2200601Ki 4500 |
| 001 - CONTROL NUMBER | |
| control field | 9781003006695 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220531132620.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
| fixed length control field | m o d |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200528s2020 xx o 000 0 eng d |
| 040 ## - Cataloging Source | |
| -- | OCoLC-P |
| -- | eng |
| -- | rda |
| -- | pn |
| -- | OCoLC-P |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781003006695 |
| -- | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1003006698 |
| -- | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781000073560 |
| -- | (electronic bk. : EPUB) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1000073564 |
| -- | (electronic bk. : EPUB) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 9780367443207 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 9780367439149 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781000073539 |
| -- | (electronic bk. : Mobipocket) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 100007353X |
| -- | (electronic bk. : Mobipocket) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781000073508 |
| -- | (electronic bk. : PDF) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1000073505 |
| -- | (electronic bk. : PDF) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 036743914X |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 0367443201 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC)1155637833 |
| Canceled/invalid control number | (OCoLC)1156472803 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC-P)1155637833 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA276.45.R3 |
| Item number | R65 2020 |
| 072 #7 - | |
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| -- | 018000 |
| -- | bisacsh |
| 072 #7 - | |
| -- | COM |
| -- | 021030 |
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| 072 #7 - | |
| -- | COM |
| -- | 021000 |
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| 072 #7 - | |
| -- | UYQ |
| -- | bicssc |
| 082 04 - | |
| -- | 005.13/3 |
| -- | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Roiger, Richard J. |
| 245 10 - TITLE STATEMENT | |
| Title | Just Enough R! : |
| Remainder of title | An Interactive Approach to Machine Learning and Analytics. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | First edition. |
| 264 #1 - | |
| -- | [Place of publication not identified] : |
| -- | Chapman and Hall/CRC, |
| -- | 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource (xviii, 346 pages). |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 505 0# - | |
| -- | Preface. Acknowledgment. Author. Introduction to Machine Learning. Introduction to R. Data Structures and Manipulation. Preparing the Data. Supervised Statistical Techniques. Tree-Based Methods. Rule-Based Techniques. Neural Networks. Formal Evaluation Techniques. Support Vector Machines. Unsupervised Clustering Techniques. A Case Study in Predicting Treatment Outcome. Bibliography. Appendix A: Supplementary Materials and More Datasets. Appendix B: Statistics for Performance Evaluation. Subject Index. Index of R Functions. Script Index. |
| 520 ## - | |
| -- | Just Enough R! An Interactive Approach to Machine Learning and Analytics presents just enough of the R language, machine learning algorithms, statistical methodology, and analytics for the reader to learn how to find interesting structure in data. The approach might be called "seeing then doing" as it first gives step-by-step explanations using simple, understandable examples of how the various machine learning algorithms work independent of any programming language. This is followed by detailed scripts written in R that apply the algorithms to solve nontrivial problems with real data. The script code is provided, allowing the reader to execute the scripts as they study the explanations given in the text. Features Gets you quickly using R as a problem-solving tool Uses RStudio's integrated development environment Shows how to interface R with SQLite Includes examples using R's Rattle graphical user interface Requires no prior knowledge of R, machine learning, or computer programming Offers over 50 scripts written in R, including several problem-solving templates that, with slight modification, can be used again and again Covers the most popular machine learning techniques, including ensemble-based methods and logistic regression Includes end-of-chapter exercises, many of which can be solved by modifying existing scripts Includes datasets from several areas, including business, health and medicine, and science About the Author Richard J. Roiger is a professor emeritus at Minnesota State University, Mankato, where he taught and performed research in the Computer and Information Science Department for over 30 years. |
| 588 ## - | |
| -- | OCLC-licensed vendor bibliographic record. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Data Processing / General |
| Source of heading or term | bisacsh |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Database Management / Data Mining |
| Source of heading or term | bisacsh |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Database Management / General |
| Source of heading or term | bisacsh |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | R (Computer program language) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data structures (Computer science) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematical statistics |
| General subdivision | Data processing. |
| 856 40 - | |
| -- | Taylor & Francis |
| -- | https://www.taylorfrancis.com/books/9781003006695 |
| 856 42 - | |
| -- | OCLC metadata license agreement |
| -- | http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
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