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

Loading the stop and frisk dataset

We will be using the diabetes dataset which was constructed in the last chapter. For some of the other decision tree examples, we will need to load the stop and frisk dataset. You can obtain this dataset from the following URL:

Select the 2015 CSV zip archive and download and extract the files to the projects directory, e.g C:/PracticalPredictiveAnalytics/Data, and name the file 2015_sqf_csv

Importing the CSV file to databricks

Databricks contains a simple user interface which allows you to load a file to the Databricks HDFS filesystem. Alternatively, you can load the file directly to Amazon Web Services (AWS) and read the file directly from the Databricks API.

  1. Switch to the Databricks application, select Tables, and then Data Import. Note that in some of the versions of Databricks this is embedded under the Data menu: Select "Tables", and then click the +.
  2. You may be prompted to create a new...