Machine Learning with R

Voorkant
Packt Publishing Ltd, 25 okt. 2013 - 396 pagina's
1 Reviewen
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.
 

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Inhoudsopgave

Downloading theexample code
Improving Model Performance
data
IntroducingMachine Learning
Finding Groups of Data Clustering with kmeans
Understanding clustering
Summary
Evaluating Model Performance Measuring performance for classification
Summary
Specialized Machine Learning Topics
Copyright

Overige edities - Alles weergeven

Veelvoorkomende woorden en zinsdelen

Over de auteur (2013)

Brett Lantz has spent the past 10 years using innovative data methods to understand human behavior. A sociologist by training, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles. Since then, he has worked on interdisciplinary studies of cellular telephone calls, medical billing data, and philanthropic activity, among others. When he's not spending time with family, following college sports, or being entertained by his dachshunds, he maintains dataspelunking.com, a website dedicated to sharing knowledge about the search for insight in data.

Bibliografische gegevens