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  • What's new or improved in Weka 3.7.5
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Core Weka

  • SGDText - stochastic gradient descent for learning linear SVMs and logistic regression for text problems. Operates incrementally and directly on string attributes.
  • New incremental version of the multi-class meta classifier (MultiClassClassifierUpdateable).
  • RandomForest now supports building trees in parallel.
  • DatabaseLoader is now much faster when loading data sets with many nominal attributes.
  • Database access now allows custom property files to be set at runtime, allowing access to databases different from the default one without having to restart Weka.
  • TextDirectoryLoader can now operate incrementally.
  • CSVLoader now supports files without a header row.
  • Charts can now be exported to files from running Knowledge Flow processes via an offscreen rendering process.
  • RemoveUseless filter now removes attributes with all missing values.
  • Histogram visualization in the Explorer and Knowledge Flow is now faster.
  • ClassifierPerformanceEvaluator in the Knowledge Flow is now multi-threaded to allow folds to be evaluated in parallel.
  • File-based savers now support gzip compression.
  • File-based loaders now support loading files as a resource from the classpath (including jars).

In Packages

  • multiInstanceLearning - added MITI multi-instance tree learner and MIRI rule learner variant.
  • RerankingSearch - a feature selection meta-search algorithm that speeds up the base search algorithm, contributed by Pablo Bermejo.
  • timeseriesForecasting package now includes support for handling timestamp-based data which contains gaps in the regular time period. Documentation here.
  • sasLoader - SAS sas7bdat file reader.
  • CHIRP - A new classifier based on Composite Hypercubes on Iterated Random Projections, contributed by Leland Wilkinson.
  • PSOSearch - An implementation of the Particle Swarm Optimization (PSO) algorithm to explore the space of attributes, contributed by Sebastian Luna Valero.
  • wekaServer - A simple servlet-based server for executing data mining tasks (Explorer and KnowledgeFlow so far). Documentation here.
  • jfreechartOffscreenRenderer - Offscreen (headless) chart rendering in Knowledge Flow processes using the JFreeChart library. More info here.
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