Mlpack

_2013-10-04_

* Cover tree support for range search (range_search), rank-approximate nearest
neighbors (allkrann), minimum spanning tree calculation (emst), and FastMKS
(fastmks).

* Dual-tree FastMKS implementation added and tested.

* Added collaborative filtering package (cf) that can provide recommendations
when given users and items.

* Fix for correctness of Kernel PCA (kernel_pca) (270).

* Speedups for PCA and Kernel PCA (198).

* Fix for correctness of Neighborhood Components Analysis (NCA) (279).

* Minor speedups for dual-tree algorithms.

* Fix for Naive Bayes Classifier (nbc) (269).

* Added a ridge regression option to LinearRegression (linear_regression)
(286).

* Gaussian Mixture Models (gmm::GMM<>) now support arbitrary covariance matrix
constraints (283).

* MVU (mvu) removed because it is known to not work (183).

* Minor updates and fixes for kernels (in mlpack::kernel).

_2013-06-13_

* Minor bugfix so that FastMKS gets built.

_2013-05-01_

* Speedups of cover tree traversers (235).

* Addition of rank-approximate nearest neighbors (RANN), found in
src/mlpack/methods/rann/.

* Addition of fast exact max-kernel search (FastMKS), found in
src/mlpack/methods/fastmks/.

* Fix for EM covariance estimation; this should improve GMM training time.

* More parameters for GMM estimation.

* Force GMM and GaussianDistribution covariance matrices to be positive
definite, so that training converges much more often.

* Add parameter for the tolerance of the Baum-Welch algorithm for HMM
training.

* Fix for compilation with clang compiler.

* Fix for k-furthest-neighbor-search.

_2013-02-08_

* Force minimum Armadillo version to 2.4.2.

* Better output of class types to streams; a class with a ToString() method
implemented can be sent to a stream with operator<<.

* Change return type of GMM::Estimate() to double (257).

* Style fixes for k-means and RADICAL.

* Handle size_t support correctly with Armadillo 3.6.2 (258).

* Add locality-sensitive hashing (LSH), found in src/mlpack/methods/lsh/.

* Better tests for SGD (stochastic gradient descent) and NCA (neighborhood
components analysis).

_2012-09-16_

* Remove internal sparse matrix support because Armadillo 3.4.0 now includes
it. When using Armadillo versions older than 3.4.0, sparse matrix support
is not available.

* NCA (neighborhood components analysis) now support an arbitrary optimizer
(245), including stochastic gradient descent (249).

_2012-08-15_

* Added density estimation trees, found in src/mlpack/methods/det/.

* Added non-negative matrix factorization, found in src/mlpack/methods/nmf/.

* Added experimental cover tree implementation, found in
src/mlpack/core/tree/cover_tree/ (157).

* Better reporting of boost::program_options errors (225).

* Fix for timers on Windows (212, 211).

* Fix for allknn and allkfn output (204).

* Sparse coding dictionary initialization is now a template parameter (220).