7f7a6868_mloss___Project_details_Mulan__Changelog
[Version] 1.3.0 [Date] May 31, 2011, 16:14:46 [Changelog] 
Learners New algorithms added in the meta package. EnsembleOfClassifierChains: The final confidences can now be computed not only by averaging votes, but also by averaging confidences. The option of sampling with replacement was added. MMP: updated with loss functions. Added possibility to specify number of training epochs for MMPLearner. BinaryRelevance: Added method to get the model built for a label. Update to the lazy package: Euclidean is still the default distance function, the option to use a different distance function is given. Measures Introduced loss functions package. Refurbished the measures package so that the measure hierarchy has cleaner semantics and takes loss functions into consideration. Strict/nostrict evaluation (handles divisions by zero differently). Uniform calculation of f-measure for all related measures. Bug fixes Bug fix in the dimensionality reduction package. Bug fix in CalibratedLabelRanking class. Updated design and bug fixes in thresholding strategies. Fixed defect in MMPUniformUpdateRule. Bug fix in the getPriors method. API changes Upgrade to Weka 3.7.3. Experiments Experiment from ICTAI 2010 paper added. Examples Simplified source examples for consistency with the online documentation. Added an example that shows storing/loading a multi-label model. Unit Tests HOMER and HMC tests added. MetaLabeler and ThresholdPrediction test updated.
mloss | Project details:Mulan
Changelog