A Python wrapper for Weka
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README.md

Weka - Python wrapper for Weka classifiers

Overview

Provides a convenient wrapper for calling Weka classifiers from Python.

Installation

First install the Weka and LibSVM Java libraries. On Debian/Ubuntu this is simply:

sudo apt-get install weka libsvm-java

Then install the Python package with pip:

sudo pip install weka

Usage

Train and test a Weka classifier by instantiating the Classifier class, passing in the name of the classifier you want to use:

from weka.classifiers import Classifier
c = Classifier(name='weka.classifiers.lazy.IBk', ckargs={'-K':1})
c.train('training.arff')
predictions = c.predict('query.arff')

Alternatively, you can instantiate the classifier by calling its name directly:

from weka.classifiers import IBk
c = IBk(K=1)
c.train('training.arff')
predictions = c.predict('query.arff')

The instance contains Weka's serialized model, so the classifier can be easily pickled and unpickled like any normal Python instance:

c.save('myclassifier.pkl')
c = Classifier.load('myclassifier.pkl')
predictions = c.predict('query.arff')