Book Image

R Programming By Example

By : Omar Trejo Navarro
Book Image

R Programming By Example

By: Omar Trejo Navarro

Overview of this book

R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.
Table of Contents (12 chapters)

Digging deeper with sentiment analysis

We have now seen that vector space operations did not work too well regarding the predictive accuracy of our model. In this section, we will attempt a technique which is very different and is closer to the semantic parsing model we mentioned at the beginning of this chapter. We will try sentiment analysis.

We will not only take into account the words in a text, but we will also take into account shifters (that is, negators, amplifiers, de-amplifiers, and adversative conjunctions). A negator flips the sign of a polarized word (for example, I do not like it). An amplifier increases the impact of a polarized word (for example, I really like it.). A de-amplifier reduces the impact of a polarized word (for example, I hardly like it). An adversative conjunction overrules the previous clause containing a polarized word (for example, I like it but...