TABLE OF CONTENTS A Machine Learning Workbench for Data Mining
Eibe Frank, Mark Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer and Ian H. Witten
Department of Computer Science, University of Waikato, Hamilton, New Zealand
{eibe, mhall, geoff, rkirkby, bernhard, ihw}@cs.waikato.ac.nz
Len Trigg
Reel Two, P O Box 1538, Hamilton, New Zealand
len@reeltwo.com
| Abstract | The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License. |
| Keywords: | machine learning software, Data Mining, data preprocessing, data visualization, extensible workbench |
Experience shows that no single machine learning method is appropriate for all possible learning problems. The universal learner is an idealistic fantasy. Real datasets vary, and to obtain accurate models the bias of the learning algorithm must match the structure of the domain.
The Weka...
