WEKA:Introduction To Weka

1. Introduction to Weka

2. Introduction Data mining isan experimental science Weka Workbench is a collection of state of the art machine learning algorithms and data processing tools It is written in java and available for Linux, Windows on Macintosh platform

3. What’s in Weka? Input is taken in the form of ARFF files Learning methods are called classifiers Classifiers have tunable parameters which you can access through a property sheet or object editor Filters are used to pre process the data

4. How to use it? There are four modes through which one can use Weka: Explorer Knowledge Flow allows you to design configurations for streamed data processing Experimenter allows an automated means to run classifiers and filters with different parameter settings on a corpus of datasets, collect performance statistics, and perform significance tests Simple CLI provides a command line mode to access Weka

5. What else is there? Weka has online documentation produced directly from the source code and describes the structure It gives list of available algorithms The application programming interface for Weka is also there Weka can be downloaded for free from http://www.cs.waikato.ac.nz/ml/weka

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