Introduction

Makes Weka algorithms available in scikit-learn.

Built on top of the python-weka-wrapper3 library, it uses the javabridge library under the hood for communicating with Weka objects in the Java Virtual Machine.

Links:

• Looking for code?

  • Project homepage

  • Example code

Requirements

The library has the following requirements:

• Python 3 (does not work with Python 2)

  • python-weka-wrapper (>=0.2.5, required)

• OpenJDK 8 or later (11 is recommended)

Contents

• Installation
• Examples
  • Start the Java Virtual Machine
  • Location of the datasets
  • Loading data
  • Regression
  • Classification
  • Clustering
  • Preprocessing
  • Data generators
  • Stop the Java Virtual Machine
  • Additional examples
• Gotchas

API

• sklweka package
  • sklweka.classifiers module
  • sklweka.clusters module
  • sklweka.dataset module
  • sklweka.preprocessing module