04431cam a2200601Ki 4500 9781003006695 FlBoTFG 20260210180854.0 m o d cr cnu|||unuuu 200528s2020 xx o 000 0 eng d OCoLC-P eng rda pn OCoLC-P 9781003006695 (electronic bk.) 1003006698 (electronic bk.) 9781000073560 (electronic bk. : EPUB) 1000073564 (electronic bk. : EPUB) 9780367443207 9780367439149 9781000073539 (electronic bk. : Mobipocket) 100007353X (electronic bk. : Mobipocket) 9781000073508 (electronic bk. : PDF) 1000073505 (electronic bk. : PDF) 036743914X 0367443201 (OCoLC)1155637833 (OCoLC)1156472803 (OCoLC-P)1155637833 QA276.45.R3 R65 2020 COM 018000 bisacsh COM 021030 bisacsh COM 021000 bisacsh UYQ bicssc 005.13/3 23 Roiger, Richard J. Just Enough R! : An Interactive Approach to Machine Learning and Analytics. First edition. [Place of publication not identified] : Chapman and Hall/CRC, 2020. 1 online resource (xviii, 346 pages). text txt rdacontent computer c rdamedia online resource cr rdacarrier 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. 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. OCLC-licensed vendor bibliographic record. COMPUTERS / Data Processing / General bisacsh COMPUTERS / Database Management / Data Mining bisacsh COMPUTERS / Database Management / General bisacsh 5215 R (Computer program language) Machine learning. 1623 Data structures (Computer science) 1661 Mathematical statistics Data processing. 1752 Taylor & Francis https://www.taylorfrancis.com/books/9781003006695 OCLC metadata license agreement http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf 93171 93170