What's new in Weka 3.7.10

Core Weka

• HoeffdingTree. Ported from the MOA implementation to a Weka classifier
• MergeInfrequentNominalValues filter
• MergeNominalValues filter. Uses an CHAID-style merging routine
• Zoom facility in the Knowledge Flow
• Epsilon-insensitive and Huber loss functions in SGD
• More CSVLoader improvements
• Class specific IR metric based evaluation in WrapperSubsetEval
• GainRatioAttributeEval now supports instance weights
• New command line option to force batch training mode when the classifier is an incremental one
• LinearRegression is now faster and more memory efficient thanks to a contribution from Sean Daugherty
• CfsSubsetEval can now use multiple CPUs/cores to pre-compute the correlation matrix (speeds up backward searches)
• GreedyStepwise can now evaluate mutliple subsets in parallel

In Packages

• New kernelLogisticRegression package
• New supervisedAttributeScaling package
• New clojureClassifier package
• localOutlierFactor now includes a wrapper classifier that uses the LOF filter
• scatterPlot3D now includes new Java3D libraries for all major platforms
• New IWSS (Incremental Wrapper Subset Selection) package contributed by Pablo Bermejo
• New MODLEM package (rough set theory based rule induction) contributed by Szymon Wojciechowski