Data Preprocessing in Data Mining

• Introduction.- Data Sets and Proper Statistical Analysis of Data Mining Techniques.- Data Preparation Basic Models.- Dealing with Missing Values.- Dealing with Noisy Data.- Data Reduction.- Feature Selection.- Instance Selection.- Discretization.- A Data Mining Software Package Including Data Preparation and Reduction: KEEL.

From the book reviews: "This book is a comprehensive collection of data preprocessing techniques used in data mining. Any readers who practice data mining will find it beneficial ... . This book is an excellent guideline in the topic of data preprocessing for data mining. It is suitable for both practitioners and researchers who would like to use datasets in their data mining projects." (Xiannong Meng, Computing Reviews, December, 2014)