Machine Learning with R Cookbook - Second Edition

Explore over 110 recipes to analyse data and build predictive models with the simple and easy-to-use R code

Machine Learning with R Cookbook - Second Edition

Ashishsingh Bhatia

Explore over 110 recipes to analyse data and build predictive models with the simple and easy-to-use R code
This title is available to pre-order now and is expected to be published in
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Book Details

ISBN 139781787284395
Paperback588 pages

Book Description

The R language is a powerful open source functional programming language. At its core, R is a statistical language that provides impressive tools to analyze data and create high-level graphics.

This book covers the basics of R by setting up a user-friendly programming environment and programming ETL in R. Data exploration examples are provided that demonstrate how powerful data visualisation and machine learning is in discovering hidden relationships. You will also explore air quality data, steps to fix the missing values and visualising the same. You will then dive into important machine learning topics, including data classification, regression, survival analysis, time series analysis, clustering association rule mining, and dimension reduction.This book will include the latest code and examples based on R 3.3 and above—updated for better computation, accuracy, and speed with R.

Table of Contents

What You Will Learn

  • Create and inspect the transaction dataset, performing association analysis with the Apriori algorithm
  • Visualize patterns and associations using a range of graphs and find frequent itemsets using the Eclat algorithm
  • Compare differences between each regression method to discover how they solve problems
  • Detect and impute missing values in air quality data
  • Predict possible churn users with the classification approach
  • Plot autocorrelation function with time series analysis
  • Use Cox proportional hazards model for survival analysis
  • Implement the clustering method to segment customer data
  • Compress images with the dimension reduction method
  • Incorporate R and Hadoop to solve machine learning problems on Big Data

Authors

Table of Contents

Book Details

ISBN 139781787284395
Paperback588 pages
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