Release 1.7.0b
Added global learning capabilities (via perceptron ranking algorithm) and tested on parser
talismane_machine_learing: added RankingModel, RankingModelTrainer, RankingEvent, RankingEventStream, RankingSolution, Ranker and FeatureWeightVector as a framework for learning projects for ranking
talismane_machine_learning: renamed generic learning classes to ClassificationModel, ClassificationModelTrainer, ClassificationEvent, ClassificationSolution to indicate they referred to classification tasks
talismane_machine_learning: rewrote ModelFactory and ModelTrainingFactory to support ranking models
talismane_machine_learning: added implementation for ranking model + trainer: PerceptronRankingModel + Parameters + Trainer + TrainerImpl
talismane_machine_learning: changed defaults for Concat and ToString: default versions don't accept nulls, need ConcatWithNulls and ToStringAllowNulls if want to accept nulls
talismane_core: added dependency labels to TransitionSystem + implementations
talismane_core: added ParsingConstrainer + implementation to check postag pairs + transition co-occurences
talismane_core: extracted ParseComparisonStrategy interface from ParseConfiguration, and created 3 implementations
talismane_core: added rewind capability to ParserAnnotatedCorpusReader + implementations, to support trainers that need full input on every iteration
talismane_core: created TransitionBasedGlobalLearning parser to use global learning mechanism for training/analysis
talismane_core: created ParseGlobalEventStream to feed RankingEvents to global learning trainer
talismane_fr: retrained all models & added default versions to talismane_fr
talismane_trainer_fr: corrected feature files to use feature name changes