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Just Enough R!: An Interactive Approach to Machine Learning and Analytics

Autor Richard J. Roiger
en Limba Engleză Hardback – 8 iun 2020
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.
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Specificații

ISBN-13: 9780367443207
ISBN-10: 0367443201
Pagini: 364
Ilustrații: 72
Dimensiuni: 178 x 254 x 21 mm
Greutate: 1.76 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC

Cuprins

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.

Notă biografică

Richard J. Roiger is a professor emeritus at Minnesota State University, Mankato where he taught and performed research in the Computer & Information Science Department for 27 years. Dr. Roiger’s Ph.D. degree is in Computer & Information Sciences from the University of Minnesota. Dr. Roiger continues to serve as a part-time faculty member teaching courses in data mining, artificial intelligence and research methods. Richard enjoys interacting with his grandchildren, traveling, writing and pursuing his musical talents.

Descriere

The main purpose of the text is to present the student with just enough of the R language, machine learning algorithms, and statistical methodology to set them on their way to a career in data science and machine learning.It is for a beginning course in machine learning, data mining & analytics, data science, or general data analysis.