A Python wrapper for the Weka data mining library.
Project description
Provides a convenient wrapper for calling Weka classifiers from Python.
Installation
Install Weka. On Debian/Ubuntu this is simply:
sudo apt-get install weka
Install the Python package:
sudo pip install -U https://github.com/chrisspen/weka/tarball/master
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')
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
weka-0.1.3.tar.gz
(14.7 kB
view hashes)
