Good luck with that. Forum for discussions around the python-weka-wrapper (PyPi, github, examples) and python-weka-wrapper3 (PyPi, github, examples) libraries. Of course, we’re cheating here a little bit, because the module does a lot of the heavy lifting, which we had to do with Jython manually. 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 Peter Reutemann shows how to bring Weka to the Python universe, and use the python-weka-wrapper library to replicate scripts from the earlier lessons. There are 14 instances - the number of rows in the table. Python-Wrapper3. Python 2.7 reaches its end-of-life in 2020 , you should consider using the Python 3 version of this library! Lesson 5.1: Invoking Python from Weka Class 1 Time series forecasting Class 2 Data stream mining in Weka and MOA Class 3 Interfacing to R and other data mining packages Class 4 Distributed processing with Apache Spark Class 5 Scripting Weka in Python Lesson 5.1 Invoking Python from Weka Lesson 5.2 Building models Lesson 5.3 Visualization Jython limits you to pure Python code and to Java libraries, and Weka provides only modeling and some limited visualization. The Objective of this post is to explain how to generate a model from ARFF data file and how to classify a new instance with this model using Weka API. This is simply with Evaluation.summary(…). For the first script, we want to revisit cross-validating a J48 classifier. This library comprises of different types of explainers depending on the kind of data we are dealing with. First of all, we’re going to start the JVM. There are many libraries in Python to perform analysis like Pandas, Matplotlib, Seaborn, etc. Explore tech trends, learn to code or develop your programming skills with our online IT courses from top universities. So far, we’ve been using Python from within the Java Virtual Machine. all systems operational. Developed and maintained by the Python community, for the Python community. Parameters: nodeCounts - an optional array that, if non-null, will hold the count of the number of nodes at which each attribute was used for splitting Returns: the average impurity decrease per attribute over the trees Throws: WekaException; listOptions public java.util.Enumeration