About: A Java framework for statistical analysis and classification of biological sequences

New classes:

• MultipleIterationsCondition: Requires another TerminationCondition to fail a contiguous, specified number of times
• ClassifierFactory: Allows for creating standard classifiers
• SeqLogoPlotter: Plot PNG sequence logos from within Jstacs
• MultivariateGaussianEmission: Multivariate Gaussian emission density for a Hidden Markov Model
• MEManager: Maximum entropy model

New features and improvements:

• Alignment: Added free shift alignment
• PerformanceMeasure and sub-classes: Extension to weighted test data
• AbstractClassifier, ClassifierAssessment and sub-classes: Adaption to weighted PerformanceMeasures
• DNAAlphabet: Parser speed-up
• PFMComparator: Extension to PFM from other sources/databases
• ToolBox: New convenience methods for computing several statistics (e.g., median, correlation)
• SignificantMotifOccurrencesFinder: New methods for computing PWMs and statistics from predictions
• SequenceScore and sub-classes: New method toString(NumberFormat)
• DataSet: Adaption to weighted data, e.g., partitioning
• REnvironment: Changed several methods from String to CharSequence

Restructuring:

• changed MultiDimensionalSequenceWrapperDiffSM to MultiDimensionalSequenceWrapperDiffSS

Several minor new features, bug fixes, and code cleanups

About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.

This release also contains several enhancements, cleanups and bugfixes:

Features

• Linear Time MMD two-sample test now works on streaming-features, which allows to perform tests on infinite amounts of data. A block size may be specified for fast processing. The below features were also added. By Heiko Strathmann.
• It is now possible to ask streaming features to produce an instance of streamed features that are stored in memory and returned as a CFeatures* object of corresponding type. See CStreamingFeatures::get_streamed_features().
• New concept of artificial data generator classes: Based on streaming features. First implemented instances are CMeanShiftDataGenerator and CGaussianBlobsDataGenerator. Use above new concepts to get non-streaming data if desired.
• Accelerated projected gradient multiclass logistic regression classifier by Sergey Lisitsyn.
• New CCSOSVM based structured output solver by Viktor Gal
• A collection of kernel selection methods for MMD-based kernel two- sample tests, including optimal kernel choice for single and combined kernels for the linear time MMD. This finishes the kernel MMD framework and also comes with new, more illustrative examples and tests. By Heiko Strathmann.
• Alpha version of Perl modular interface developed by Christian Montanari.
• New framework for unit-tests based on googletest and googlemock by Viktor Gal. A (growing) number of unit-tests from now on ensures basic funcionality of our framework. Since the examples do not have to take this role anymore, they should become more ilustrative in the future.
• Changed the core of dimension reduction algorithms to the Tapkee library.

Bugfixes

• Fix for shallow copy of gaussian kernel by Matt Aasted.
• Fixed a bug when using StringFeatures along with kernel machines in cross-validation which cause an assertion error. Thanks to Eric (yoo)!
• Fix for 3-class case training of MulticlassLibSVM reported by Arya Iranmehr that was suggested by Oksana Bayda.
• Fix for wrong Spectrum mismatch RBF construction in static interfaces reported by Nona Kermani.
• Fix for wrong include in SGMatrix causing build fail on Mac OS X (thanks to @bianjiang).
• Fixed a bug that caused kernel machines to return non-sense when using custom kernel matrices with subsets attached to them.
• Fix for parameter dictionary creationg causing dereferencing null pointers with gaussian processes parameter selection.
• Fixed a bug in exact GP regression that caused wrong results.
• Fixed a bug in exact GP regression that produced memory errors/crashes.
• Fix for a bug with static interfaces causing all outputs to be -1/+1 instead of real scores (reported by Kamikawa Masahisa).

Cleanup and API Changes

• SGStringList is now based on SGReferencedData.
• "confidences" in context of CLabel and subclasses are now "values".
• CLinearTimeMMD constructor changes, only streaming features allowed.
• CDataGenerator will soon be removed and replaced by new streaming- based classes.
• SGVector, SGMatrix, SGSparseVector, SGSparseVector, SGSparseMatrix refactoring: Now contains load/save routines, relevant functions from CMath, and implementations went to .cpp file.