Data Mining: Practical Machine Learning Tools and Techniques

Data mining is not an intuitive activity. It requires skills and techniques which can be honed by using books like data mining: practical machine learning tools and techniques. This book is an ultimate guide for applying machine learning techniques and tools in real-world situations of data mining. The book will help you interpret outputs, evaluate results and prepare inputs and will provide the algorithmic methods for efficient data mining. You will not only find the explanation of concepts in this book but will also come across practical advice for successful data mining. Data mining: practical machine learning tools and techniques in the new edition includes all the recent changes and modernisation of techniques of data mining. You will find extra material on ensemble learning, data transformation, massive data sets and multi-instance learning. The book also includes weka software for machine learning that the authors have developed. Authors ian h. Witten, mark a hall and eibe frank have included the tried and tested methods of data mining in this book, along with the toolkit of weka software having an interactive interface, data classification, clustering, visualisation and association rules. Data mining: practical machine learning tools and techniques is now available in its third edition in paperback by elsevier. Key features: data mining: practical machine learning tools and techniques includes latest material on new modernization tools and techniques. The book also includes the downloadable software and toolkit of the popular data mining software weka, created by the authors. It illustrates machine learning concepts of data mining and provides practical suggestions on effective data mining techniques.