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

Input, output, and predicted columns


You are familiar with the predictable columns from Chapter 2, Data Model Preparation and Deployment, but let's talk briefly about the input, output, and predicted columns in this chapter.

Input columns are the columns whose value is used as an input to the data mining model to predict an output. If a column is marked Predict Only, the columns are both predictable and output columns, but if a column is marked Predict, then the column is both an input and output column.