Book Image

Mastering SQL Server 2014 Data Mining

By : Amarpreet Singh Bassan, Debarchan Sarkar
Book Image

Mastering SQL Server 2014 Data Mining

By: Amarpreet Singh Bassan, Debarchan Sarkar

Overview of this book

<p>Whether you are new to data mining or are a seasoned expert, this book will provide you with the skills you need to successfully create, customize, and work with Microsoft Data Mining Suite. Starting with the basics, this book will cover how to clean the data, design the problem, and choose a data mining model that will give you the most accurate prediction.</p> <p>Next, you will be taken through the various classification models such as the decision tree data model, neural network model, as well as Naïve Bayes model. Following this, you'll learn about the clustering and association algorithms, along with the sequencing and regression algorithms, and understand the data mining expressions associated with each algorithm. With ample screenshots that offer a step-by-step account of how to build a data mining solution, this book will ensure your success with this cutting-edge data mining system.</p>
Table of Contents (17 chapters)
Mastering SQL Server 2014 Data Mining
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 6. Segmentation and Association Models

In the previous chapter, you had an extensive look at the classification models. There are business requirements wherein the answer is not yes/no, but rather finding a relationship between the entities. A common example of this can be looking for similarity in the employees with a particular tenure in an organization or products bought by a section of society. The Microsoft Clustering algorithm helps us group the entities with the same attributes and study their common behavior, be it determining the buying patterns of one section of society or the investing patterns of a different one. The Microsoft Association algorithm helps us determine the placement of the products in a supermarket or helps suggest some additional products to the customer based on their purchase. We will alter their parameters to see the change in their behavior. At the end of this chapter, you will be able to use these algorithms to solve a business problem targeted towards...