Practical Machine Learning in R (2021 Update)

Do you want to start using R for crunching machine learning models right from the start with examples? Then this book is

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English Pages 160 Year 2018

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Table of contents :
Title Page
Table of Contents
Part I - Introduction
Chapter 1 - Introduction to R
Chapter 2 - Introduction to Machine Learning
Part II - Classification
Chapter 3 - Classification with Decision trees
Chapter 4 - Classification with Naive Bayes
Chapter 5 - Classification with k-Nearest Neighbors
Chapter 6 - Classification with Support Vector Machines
Part III - Data Processing
Chapter 7 - Feature Selection
Chapter 8 - Dimensionality Reduction
Part III - Clustering
Chapter 9 - Centroid-based Clustering and Evaluation
Chapter 10 - Connectivity-based Clustering
Chapter 11 Density-based Clustering
Chapter 12 - Distribution-based Clustering
Part V - Extended Topics
Chapter 13 - Association Rules

Practical Machine Learning in R (2021 Update)

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