North Matthew A. Data Mining for the Masses

Global Text Project, 2012. — 252 p.The intent of this book is to introduce you to concepts and practices common in data mining. It is intended primarily for undergraduate college students and for business professionals who may be interested in using information systems and technologies to solve business problems by mining data, but who likely do not have a formal background or education in computer science. Although data mining is the fusion of applied statistics, logic, artificial intelligence, machine learning and data management systems, you are not required to have a strong background in these fields to use this book. While having taken introductory college-level courses in statistics and databases will be helpful, care has been taken to explain within this book, the necessary concepts and techniques required to successfully learn how to mine data.Data Mining Basics
Introduction to Data Mining and CRISP-DM
Organizational Understanding and Data Understanding
Data Preparation
Data Mining Models and Methods
Correlation
Association Rules
k-Means Clustering
Discriminant Analysis
Linear Regression
Logistic Regression
Decision Trees
Neural Networks
Text Mining
Special Considerations in Data Mining
Evaluation and Deployment
Data Mining Ethics