Book Image

Big Data Analytics with R

By : Simon Walkowiak
Book Image

Big Data Analytics with R

By: Simon Walkowiak

Overview of this book

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.
Table of Contents (16 chapters)
Big Data Analytics with R
About the Author
About the Reviewers

Chapter 8. Machine Learning Methods for Big Data in R

So far in this book we have explored a variety of descriptive and diagnostic statistical methods that can easily be applied to out-of-memory data sources. But the true potential of modern data science resides in its predictive and prescriptive abilities. In order to harness them, versatile data scientists should understand the logic and implementations of techniques and methods commonly known as machine learning algorithms, that allow making robust predictions and foreseeing patterns of events. In this chapter we will introduce you to machine learning methods that are applicable to Big Data classification and clustering problems through the syntax of the R language. Moreover, the contents of this chapter will provide you with the following skills:

  • You will understand the concept of machine learning and be able to distinguish between supervised/unsupervised methods and clustering/classification models

  • You will carry out a high...