Home > Releases > Cognitive Foundry 3.3.1 Released

Cognitive Foundry 3.3.1 Released

October 6th, 2011

Version 3.3.1 of the Cognitive Foundry is released. Go and download it now. Here is the list of changes:

Release 3.3.1 (2011-10-06):

  * Common Core:
    * Added NumericMap interface, which provides a mapping of keys to numeric
    * Added ScalarMap interface, which extends NumericMap to provide a mapping
      of objects to scalar values represented as doubled.
    * Added AbstractScalarMap and AbstractMutableDoubleMap to provide abstract,
      partial implementations of the ScalarMap interface.
    * Added VectorSpace interface, where a VectorSpace is a type of Ring that
      you can perform Vector-like operations on such as norm, distances, etc.
    * Added AbstractVectorSpace, which provides an abstract, partial
      implementation of the VectorSpace interface.
    * Updated Vector, AbstractVector, VectorEntry to build on new VectorSpace
      interface and AbstractVectorSpace class.
    * Added InfiniteVector interface, which has a potentially infinite number
      of indices, but contains only a countable number in any given instance.
    * Added DefaultInfiniteVector, an implementation of the InfiniteVector
      interface backed by a LinkedHashMap.
    * Rewrote FiniteCapacityBuffer from the ground up, now with backing from a
      fixed-size array to minimize memory allocation.
    * Renamed IntegerCollection to IntegerSpan.
  * Learning Core:
    * Updated ReceiverOperatingCharacteristic to improve calculation
    * Added PriorWeightedNodeLearner interface, which provides for configuring the
      prior weights on the learning algorithm that searches for a decision
      function inside a decision tree.
    * Updated AbstractDecisionTreeNode to fix off by one error in computing node's
    * Updated CategorizationTreeLearner to add ability to specify class priors
      for decision tree algorithm.
    * Updated VectorThresholdInformationGainLearner to add class priors to
      information gain calculation.
    * Updated SequentialMinimalOptimization to improve speed.
    * Added LinearBasisRegression, which uses a basis function to generate
      vectors before performing a LinearRegression.
    * Added MultivariateLinearRegression, which performs multivariate regression;
      does not explicitly estimate a bias term or perform regularization.
    * Added LinearDiscriminantWithBias, which provides a LinearDiscriminant with
      an additional bias term that gets added to the output of the dot product.
    * Updated LinearRegression and LogisticRegression to provide for bias term
      estimation and use of L2 regularization.
    * Renamed SquashedMatrixMultiplyVectorFunction to GeneralizedLinearModel.
    * Renamed DifferentiableSquashedMatrixMultiplyVectorFunction to
    * Renamed MatrixMultiplyVectorFunction to MultivariateDiscriminant.
    * Added MultivariateDiscriminantWithBias, which provides a multivariate
      discriminant with a bias term.
    * Renamed DataHistogram to DataDistribution.
    * Renamed AbstractDataHistogram to AbstractDataDistribution.
    * Added DefaultDataDistribution, a default implementation of the
      DataDistribution interface that uses a backing map.
    * Added LogisticDistribution, an implementation of the scalar logistic
    * Updated MultivariateGaussian to provide for incremental estimation of
      covariance-matrix inverse without a single matrix inversion.
    * Removed DecoupledVectorFunction.
    * Removed DecoupledVectorLinearRegression.
    * Removed PointMassDistribution.
    * Removed MapBasedDataHistogram.
    * Removed MapBasedPointDistribution.
    * Removed MapBasedSortedDataHistogram.
    * Removed AbstractBayseianRegression.
    * Additional general reworking and clean up of distribution code,
      impacting classes in gov.sandia.cognition.statistics.distribution
  * Text Core:
    * Renamed LatentDirichetAllocationVectorGibbsSampler to
      LatentDirichletAllocationVectorGibbsSampler to fix misspelling.
    * Added ParallelLatentDirichletAllocationVectorGibbsSampler, a parallelized
      version of Latent Dirichlet Allocation.

We’ll try to get it up in Maven central soon.

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