Introduction to statistical training with examples in R language
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The book is an accessible Introduction to Statistical Training - an indispensable set of tools that make it possible to extract useful information from large and complex data sets that began to occur in the last 20 years in areas such as biology, economics, marketing, physics, etc. in this book Some of the most important methods of modeling and forecasting, as well as examples of their practical application are described. Threaded topics include linear regression, classification, creation of repeated samples, regularization, decisions, support vectors, clustering, etc. Description of these methods is accompanied by numerous illustrations and practical examples. Since the purpose of this textbook is to promote methods of statistical training among practitioners of academic researchers and industrial analysts, each chapter includes examples of the practical implementation of the appropriate methods using the R - an extremely popular environmental computing environment with open source.
The publication is designed for non-specialists who would like to apply modern methods of statistical training for analyzing their data. It is assumed that readers previously listened only to a course on linear regression and do not possess knowledge of the matrix algebra
The publication is designed for non-specialists who would like to apply modern methods of statistical training for analyzing their data. It is assumed that readers previously listened only to a course on linear regression and do not possess knowledge of the matrix algebra
Author:
Author:James Garet
Cover:
Cover:Hard
Category:
- Category:Business & Money
- Category:Science & Math
ISBN:
ISBN:978-5-97060-293-5
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