Book Image

Practical Predictive Analytics

By : Ralph Winters
Book Image

Practical Predictive Analytics

By: Ralph Winters

Overview of this book

This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a description of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data.
Table of Contents (19 chapters)
Title Page
About the Author
About the Reviewers
Customer Feedback


R, like many languages and knowledge discovery systems, started from the command line. However, predictive analysts tend to prefer Graphic User Interfaces (GUIs), and there are many choices available for each of the three different operating systems (Mac, Windows, and Linux). Each of them has its strengths and weaknesses, and of course there is always the question of preference.

Memory is always a consideration with R, and if that is of critical concern to you, you might want to go with a simpler GUI, such as the one built in with R.

If you want full control, and you want to add some productive tools, you could choose RStudio, which is a full-blown GUI and allows you to implement version control repositories, and has nice features such as code completion.

R Commander (Rcmdr), and Rattle unique features are that they offer menus that allow guided point and click commands for common statistical and data mining tasks. They are always both code generators. This is a way to start when learning R, since you can use the menus to accomplish the tasks, and then by looking at the way the code was generated for each particular task. If you are interested in predictive analytics using Rattle, I have written a nice tutorial on using R with Rattle which can be found in the tutorial section of Practical Predictive Analytics and Decisioning Systems for Medicine, which is referenced at the end of this chapter.

Both RCmdr and RStudio offer GUIs that are compatible with the Windows, Apple, and Linux operator systems, so those are the ones I will use to demonstrate examples in this book. But bear in mind that they are only user interfaces, and not R proper, so it should be easy enough to paste code examples into other GUIs and decide for yourself which ones you like.