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...DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. License: R, RStudio, NLTK, SciPy, SKLearn, MatPlotLib, Weka, ... each has their own licenses.

LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.

This is a GUI for learning non disjoint groups of documents based on Weka machine learning framework. It offers the possibility to make non disjoint clustering of documents using both vectorial and sequential representation (word sequence approach based on WSK kernel). All data format supported by WEKA could be used in DocCO. Data could be loaded from files, from databases or from specified URL. All the preprocessing techniques implemented in WEKA could be used before performing the learning.

BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.

weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.