Cognitive Foundry version 3.4.2 released
October 29th, 2015
This version contains several new components, performance enhancements, and an upgraded version of MTJ. You can download it directly here or from Maven Central through dependency management tools like Ivy and Maven.
Release notes: * General: * Upgraded MTJ to 1.0.3. * Common: * Added package for hash function computation including Eva, FNV-1a, MD5, Murmur2, Prime, SHA1, SHA2 * Added callback-based forEach implementations to Vector and InfiniteVector, which can be faster for iterating through some vector types. * Optimized DenseVector by removing a layer of indirection. * Added method to compute set of percentiles in UnivariateStatisticsUtil and fixed issue with percentile interpolation. * Added utility class for enumerating combinations. * Adjusted ScalarMap implementation hierarchy. * Added method for copying a map to VectorFactory and moved createVectorCapacity up from SparseVectorFactory. * Added method for creating square identity matrix to MatrixFactory. * Added Random implementation that uses a cached set of values. * Learning: * Implemented feature hashing. * Added factory for random forests. * Implemented uniform distribution over integer values. * Added Chi-squared similarity. * Added KL divergence. * Added general conditional probability distribution. * Added interfaces for Regression, UnivariateRegression, and MultivariateRegression. * Fixed null pointer exception that can happen in K-means with an empty cluster. * Fixed name of maxClusters property on AgglomerativeClusterer (was called maxMinDistance). * Text: * Improvements to LDA Gibbs sampler.