WEKA-Tutorial

WEKAMachine Learning Algorithms in JavaIan H. WittenDepartment of Computer ScienceUniversity of WaikatoHamilton, New ZealandE-mail: ihw@cs.waikato.ac.nzEibe FrankDepartment of Computer ScienceUniversity of WaikatoHamilton, New ZealandE-mail: eibe@cs.waikato.ac.nzThis tutorial is Chapter 8 of the book Data Mining: Practical Machine LearningTools and Techniques with Java Implementations. Cross-references are to othersections of that book.© 2000 Morgan Kaufmann Publishers. All rights reserved.c h a p t e r e i g h t Nuts and bolts: Machinelearning algorithms in Javall the algorithms discussed in this book have been implemented andmade freely available on the World Wide Web (www.cs.waikato.ac.nz/ml/weka) for you to experiment with. This will allow you toAlearn more about how they work and what they do. Theimplementations are part of a system called Weka, developed at theUniversity of Waikato in New Zealand. “Weka” stands for the WaikatoEnvironment for Knowledge Analysis. (Also, the weka, pronounced torhyme with Mecca, is a flightless bird with an inquisitive nature found onlyon the islands of New Zealand.) The system is written in Java, an object-oriented programming language that is widely available for all majorcomputer platforms, and Weka has been tested under Linux, Windows, andMacintosh operating systems. Java allows us to provide a uniform interfaceto many different learning algorithms, along with methods for pre- andpostprocessing and ...