What's new in Weka 3.8.0 and 3.9.0
- Former user (Deleted)
Owned by Former user (Deleted)
In core weka
- JAMA-based linear algebra routines replaced with MTJ. Faster operation with the option to use native libraries for even more speed
- General efficiency improvements in core, filters and some classifiers
- GaussianProcesses now handles instance weights
- New Knowledge Flow implementation. Engine completely rewritten from scratch with a simplified API
- New Workbench GUI
- GUI package manager now has a search facility
- FixedDictionaryStringToWordVector filter allows the use of an external dictionary for vectorization. DictionarySaver converter can be used to create a dictionary file
In packages
- Packages that were using JAMA are now using MTJ
- New netlibNativeOSX, netlibNativeWindows and netlibNativeLinux packages providing native reference implementations (and system-optimized implementation in the case of OSX) of BLAS, LAPACK and ARPACK linear algebra
- New elasticNet package, courtesy of Nikhil Kinshore
- New niftiLoader package for loading a directory with MIR data in NIfTI format into Weka
- New percentageErrorMetrics package - provides plugin evaluation metrics for root mean square percentage error and mean absolute percentage error
- New iterativeAbsoluteErrorRegression package - provides a meta learner that fits a regression model to minimize absolute error
- New largeScaleKernelLearning package - contains filters for large-scale kernel-based learning
- discriminantAnalysis package now contains an implementation for LDA and QDA
- New Knowledge Flow component implementations in various packages
- newKnowledgeFlowStepExamples package - contains code examples for new Knowledge Flow API discussion in the Weka Manual
- RPlugin updated to latest version of MLR
- scatterPlot3D and associationRulesVisualizer packages updated with latest Java 3D libraries
- Support for pluggable activation functions in the multiLayerPerceptrons package