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