Title: What This Book is About and What It is Not
Summary
The first chapter of this book introduces the basic concepts of data mining and machine learning, common terms used in the field and throughout this book, and the decision tree modeling technique as a machine learning technique for classification tasks. The second chapter gives you an introductory tour through the RapidMiner graphical user interface (GUI) and how to use it to define data mining processes. In case you are already familiar with data mining and RapidMiner, you can skip these two chapters. However, if you are a novice in the field or regarding the software, these first two chapters are highly recommended and will give you a quick start in both data mining and RapidMiner. All following chapters provide a use case each and introduce additional data mining concepts and RapidMiner operators needed to solve the task at hand.
Table of Contents:
1.1 Introduction
1.2 Coincidence or Not?
1.3 Applications of Data Mining
1.3.1 Financial Services
1.3.2 Retail and Consumer Products
1.3.3 Telecommunications and Media
1.3.4 Manufacturing, Construction, and Electronics
1.4 Fundamental Terms
1.4.1 Attributes and Target Attributes
1.4.2 Concepts and Examples
1.4.3 Attribute Roles
1.4.4 Value Types
1.4.5 Data and Meta Data
1.4.6 Modeling
Datasets: None required