Release Notes: This release adds fixes compilation on a few older compilers and adds some new functionality on Multidimensional scaling.
Release Notes: The most important change is the inclusion of eigen in the source distribution, which makes milk easier to compile. In addition, this release adds subspace projection k-nearest neighbours and mds_dists functionality.
Release Notes: This release adds coordinate descent-based LASSO and makes SVM classification much faster (a 2.5x speedup on the yeast UCI dataset).
Release Notes: This release fixes a bug in adaboost and adds a few extra small functions such as zscoring on multiple axes, Euclidean multi-dimensional scaling, and tree-based multi-class learning.
Release Notes: Interfaces are more consistent (learners ignore arguments they cannot use and the default model supports the apply_many method). There are many improvements and bugfixes.
Release Notes: An important bug that slipped into 0.4.0 was fixed. This bug meant that the new implementation of gridsearch could potentially return the wrong result.
Release Notes: New features: parallel processing, perceptron, and error correcting output codes. Enhancements: setting the random seed in random forests, a 'multi_strategy' parameter for defaultlearner(), a return value from gridminimise, faster dot-kernel SVMs, and sigmoidal fitting. A bugfix in randomforest.
Release Notes: The new milk.ext.jugparallel module was added to interface with jug (http://luispedro.org/software/jug). This makes it easy to parallelize things such as n-fold cross validation (each fold runs on its own processor) or multiple kmeans random starts. Some new functions were added: measures.curves.precision_recall, milk.unsupervised.kmeans.select_best.kmeans. A tricky bug in SDA and a few minor issues elsewhere were fixed.
Release Notes: Many speed improvements. Some bugfixes (to gridminimize and tree learning). A few new utility functions.
Release Notes: Compilation on Windows was fixed.