From the reviews: "This is a comprehensive book about knowledge discovery methods. ... the book is highly recommended to final year undergraduate students, postgraduate students and lecturers. ... it has a good balance of various topics making it a good reference book for practitioners, such as data modellers, insight analysts, fraud analysts, etc., as well as researchers. ... this book is very well organized and presented. ... I would certainly recommend it to those with intermediate or advanced understanding of data-mining topics." (Boran Gazi, The Computer Journal, Vol. 53 (4), 2010)

• Data Mining and Knowledge Discovery Process.- The Knowledge Discovery Process.- Data Understanding.- Data.- Concepts of Learning, Classification, and Regression.- Knowledge Representation.- Data Preprocessing.- Databases, Data Warehouses, and OLAP.- Feature Extraction and Selection Methods.- Discretization Methods.- Data Mining: Methods for Constructing Data Models.- Unsupervised Learning: Clustering.- Unsupervised Learning: Association Rules.- Supervised Learning: Statistical Methods.- Supervised Learning: Decision Trees, Rule Algorithms, and Their Hybrids.- Supervised Learning: Neural Networks.- Text Mining.- Data Models Assessment.- Assessment of Data Models.- Data Security and Privacy Issues.- Data Security, Privacy and Data Mining.

From the reviews: "This is a comprehensive book about knowledge discovery methods. ... the book is highly recommended to final year undergraduate students, postgraduate students and lecturers. ... it has a good balance of various topics making it a good reference book for practitioners, such as data modellers, insight analysts, fraud analysts, etc., as well as researchers. ... this book is very well organized and presented. ... I would certainly recommend it to those with intermediate or advanced understanding of data-mining topics." (Boran Gazi, The Computer Journal, Vol. 53 (4), 2010)

• Data Mining and Knowledge Discovery Process.- The Knowledge Discovery Process.- Data Understanding.- Data.- Concepts of Learning, Classification, and Regression.- Knowledge Representation.- Data Preprocessing.- Databases, Data Warehouses, and OLAP.- Feature Extraction and Selection Methods.- Discretization Methods.- Data Mining: Methods for Constructing Data Models.- Unsupervised Learning: Clustering.- Unsupervised Learning: Association Rules.- Supervised Learning: Statistical Methods.- Supervised Learning: Decision Trees, Rule Algorithms, and Their Hybrids.- Supervised Learning: Neural Networks.- Text Mining.- Data Models Assessment.- Assessment of Data Models.- Data Security and Privacy Issues.- Data Security, Privacy and Data Mining.

From the reviews: "This is a comprehensive book about knowledge discovery methods. ... the book is highly recommended to final year undergraduate students, postgraduate students and lecturers. ... it has a good balance of various topics making it a good reference book for practitioners, such as data modellers, insight analysts, fraud analysts, etc., as well as researchers. ... this book is very well organized and presented. ... I would certainly recommend it to those with intermediate or advanced understanding of data-mining topics." (Boran Gazi, The Computer Journal, Vol. 53 (4), 2010)

• Data Mining and Knowledge Discovery Process.- The Knowledge Discovery Process.- Data Understanding.- Data.- Concepts of Learning, Classification, and Regression.- Knowledge Representation.- Data Preprocessing.- Databases, Data Warehouses, and OLAP.- Feature Extraction and Selection Methods.- Discretization Methods.- Data Mining: Methods for Constructing Data Models.- Unsupervised Learning: Clustering.- Unsupervised Learning: Association Rules.- Supervised Learning: Statistical Methods.- Supervised Learning: Decision Trees, Rule Algorithms, and Their Hybrids.- Supervised Learning: Neural Networks.- Text Mining.- Data Models Assessment.- Assessment of Data Models.- Data Security and Privacy Issues.- Data Security, Privacy and Data Mining.