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Machine Learning with R Cookbook - (Paperback, 2nd Revised edition)
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Machine Learning with R Cookbook - (Paperback, 2nd Revised edition)
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Explore over 110 recipes to analyze data and build predictive
models with simple and easy-to-use R code About This Book * Apply R
to simplify predictive modeling with short and simple code * Use
machine learning to solve problems ranging from small to big data *
Build a training and testing dataset, applying different
classification methods. Who This Book Is For This book is for data
science professionals, data analysts, or people who have used R for
data analysis and machine learning who now wish to become the go-to
person for machine learning with R. Those who wish to improve the
efficiency of their machine learning models and need to work with
different kinds of data set will find this book very insightful.
What You Will Learn * Create and inspect transaction datasets and
perform association analysis with the Apriori algorithm * Visualize
patterns and associations using a range of graphs and find frequent
item-sets 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 the
autocorrelation function with time series analysis * Use the 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 In Detail Big data has become
a popular buzzword across many industries. An increasing number of
people have been exposed to the term and are looking at how to
leverage big data in their own businesses, to improve sales and
profitability. However, collecting, aggregating, and visualizing
data is just one part of the equation. Being able to extract useful
information from data is another task, and a much more challenging
one. Machine Learning with R Cookbook, Second Edition uses a
practical approach to teach you how to perform machine learning
with R. Each chapter is divided into several simple recipes.
Through the step-by-step instructions provided in each recipe, you
will be able to construct a predictive model by using a variety of
machine learning packages. In this book, you will first learn to
set up the R environment and use simple R commands to explore data.
The next topic covers how to perform statistical analysis with
machine learning analysis and assess created models, covered in
detail later on in the book. You'll also learn how to integrate R
and Hadoop to create a big data analysis platform. The detailed
illustrations provide all the information required to start
applying machine learning to individual projects. With Machine
Learning with R Cookbook, machine learning has never been easier.
Style and approach This is an easy-to-follow guide packed with
hands-on examples of machine learning tasks. Each topic includes
step-by-step instructions on tackling difficulties faced when
applying R to machine learning.
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