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Introduction to Classifier Performance Analysis with R by Saw, Sutaip L.C. is a nonfiction available to read on EtoBox.

What is Introduction to Classifier Performance Analysis with R about?

Classification problems are common in business, medicine, science, engineering, and other sectors of the economy. Data scientists and machine learning professionals solve these problems through the use of classifiers. Choosing one of these data-driven classification algorithms for a given problem is a challenging task. An important aspect involved in this task is classifier performance analysis (CPA). Introduction to Classifier Performance Analysis with R provides an introductory account of commonly used CPA techniques for binary and multiclass problems, and use of the R software system to accomplish the analysis. Coverage draws on the extensive literature available on the subject, including descriptive and inferential approaches to CPA. Exercises are included at the end of each chapter to reinforce learning. Key Features: An introduction to binary and multiclass classification problems is provided, including some classifiers based on statistical, machine, and ensemble learning. Commonly used techniques for binary and multiclass CPA are covered, some from less well-known but useful points of view. Coverage also includes important topics that have not received much attention in text

Who reads Introduction to Classifier Performance Analysis with R?

Author

Saw, Sutaip L.C.

Publisher

CRC Press

Published

2024

Language

EN

Category

nonfiction

Subjects

Computer Science, Organization And Data Processing, Stem