About:
A Java framework for statistical analysis and classification of biological sequences
Changes:
February 2, 2012:
Jstacs 2.0 released
Jstacs 2.0 changes many names and the structure of several packages. It is not code-compatible with Jstacs 1.5 and earlier
RESTRUCTURING and RENAMING:
former ScoringFunction, NormalizableScoringFunction, Model
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new base-interface SequenceScore
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new sub-interface StatisticalModel of SequenceScore for all statistical models with sub-iterfaces DifferentiableStatisticalModel and TrainableStatisticalModel
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new interface DifferentiableSequenceScore replaces ScoringFunction
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new interface DifferentiableStatisticalModel replaces NormalizableScoringFunction
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new interface TrainableStatisticalModel replaces Model
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new abstract class AbstractDifferentiableSequenceScore
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new abstract class AbstractDifferentiableStatisticalModel replaces AbstractNormalizableScoringFunction
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new abstract class AbstractTrainableStatisticalModel replaces AbstractModel
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former Models renamed to TrainSM
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former ScoringFunction renamed to DiffSS or DiffSM
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getProbFor removed from TrainableStatisticalModel (former Model) and conceptually replaced by getLogProbFor
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getLogScore(Sequence,int,int) with changed meaning of arguments: getLogScore(Sequence,start,end) instead of getLogScore(Sequence,start,length)
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isTrained() replaced by common method isInitialized()
Parameters and Results
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new super-class of Parameters and Results: AnnotatedEntity
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common list-type for Parameters and Results: AnnotatedEntityList
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Renaming: CollectionParameter -> SelectionParameter, MultiSelectionCollectionParameter -> MultiSelectionParameter, new super-class AbstractSelectionParameter
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major refactoring due to common hierarchy and code-cleanup
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lazy evaluation of Parameter/ParameterSet hierarchies moved from ParameterSet (loadParameters()) to ParameterSetContainer (constructor on class)
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SubclassFinder adapted to lazy evaluation
performance measures
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new abstract super-class AbstractPerformanceMeasure of all performance measures
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new interface NumericalPerformanceMeasure for all performance measures that return a single number (as opposed, e.g., to curves)
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new class PerformanceMeasureParameterSet for a collection of general performance measures
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new class NumericalPerformanceMeasureParameterSet for a collection of NumericalPerformanceMeasures
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used in evaluate-method of AbstractClassifier and in ClassifierAssessments
further changes
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Sample renamed to DataSet
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evaluate and evaluateAll in AbstractClassifier joined
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new class IndependentProductDiffSS as super-class of IndepedentProductDiffSM (former IndependentProductScoringFunction)
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new class UniformDiffSS as super-class of UniformDiffSM (former UniformScoringFunction)
NEW FUNCTIONALITY:
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multi-threaded implementation of Baum-Welch and Viterbi training of hidden Markov models
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new Interface Singleton that can be used for singleton instances to save memory, current examples: DNAAlphabet, DNAAlphabetContainer, ProteinAlphabet
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added ProteinAlphabet
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added possibility to use NaN-values with ContinuousAlphabets
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added ArbitraryFloatSequence including static methods for DataSet creation for cases where double-precision is not needed
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new performance measure MaximumFMeasure
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access to Parameters in ParameterSets and Results in ResultSets by name
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emitDataSet in BayesianNetworkDiffSM
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new static method Time.getTimeInstance that returns UserTime or RealTime depending on availability of shared lib
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SubclassFinder allows for adding own base packages
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new method overlaps() in LocatedSequenceAnnotationWithLength
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AbstractTerminationCondition used in ScoreClassifier and sub-classes
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public method propagateESS in HMMFactory
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new method generateLog in DirichletMRG for drawing log-values
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added DifferentiableStatisticalModelFactory
BUGFIXES/IMPROVEMENTS:
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bugfix in propagation of equivalent sample size in HMMFactory
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bugfix in random initialization of BasicHigherOrderTransition
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improved Alignment implementation
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SafeOutputStream with new static factory method getSafeOutputStream, write methods now work on Objects
DOCUMENTATION:
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improved Javadocs in many classes and packages
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new Cookbook with extensive documentation and explanation
MISC:
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output of NonParsableException more verbose
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Exceptions in multi-threaded code now lead to exit of program instead of only stopping the thread
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update of RServe/RClient
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- Operating System:
Cygwin,
Linux,
Macosx,
Windows,
Unix,
Agnostic,
Solaris,
Freebsd,
Platform Independent
- Data Formats:
Plain Ascii,
Fasta
- JMLR-MLOSS Publication:
JMLR Page
- Tags:
Bioinformatics,
R,
Classification,
Machine Learning,
Bayesian Networks,
Markov Random Fields,
Supervised Learning,
Em,
Mixture Models,
Java,
Learning Principles,
Probabilistic Models,
Motif Discovery
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