It contains information about data being annealed and its various properties. Annealing dataset is from the UCI repository of datasets.Discretization, normalization, resampling, attribute selection, transforming, combining attributes, etc.Pre-processing tools in WEKA are called “filters”.A more thorough description is available here Numeric attribute nominal attribute WEKA:: ARRF file format anneal carbon hardness 'enamelability' Data can also be read from a URL or from an SQL database (using JDBC).Data can be imported from a file in various formats:.Can work with a wide variety of data files including its own “.arff” format and C4.5 file formats.Uses flat text files to describe the data.Weka routines can be used stand alone via the command line.Routines are implemented as classes and logically arranged in packages.setenv CLASSPATH $WEKAHOME/weka.jar:$CLASSPATH.setenv WEKAHOME /usr/local/weka/weka-3-6-1.Set the weka environment variable for java.If you are interested in modifying/extending weka there is a developer version that includes the source code.

Created by researchers at the University of Waikato in New Zealand.A collection of open source ML algorithms.

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