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 values. * 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 depth. * 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 DifferentiableGeneralizedLinearModel. * 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 distribution. * 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 package. * 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.