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

Summarizing the metrics

Running a summary on the rules_clust object indicates an average support of 0.05, and average confidence of 0.43.

This demonstrates that using clustering can be a viable way to develop association rules, and reduce resources and the number of dimensions at the same time:

    support          confidence           lift     
 Min.   :0.02044   Min.   :0.09985   Min.   :0.989 
 1st Qu.:0.02664   1st Qu.:0.19816   1st Qu.:1.006 
 Median :0.03066   Median :0.27143   Median :1.526 
 Mean   :0.05040   Mean   :0.43040   Mean   :1.608 
 3rd Qu.:0.04234   3rd Qu.:0.81954   3rd Qu.:1.891 
 Max.   :0.17080   Max.   :1.00000   Max.   :3.022