Milk
Milk is a machine learning toolkit in Python. Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, and decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. For unsupervised learning, milk supports k-means clustering and affinity propagation.
| Tags | machine learning Python Numpy |
|---|---|
| Licenses | MIT/X |
| Operating Systems | Cross Platform |
| Implementation | Python C++ |
Recent releases
- 17 Jan 2013 22:08
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.
- 08 Nov 2012 02:44
Release Notes: This release adds coordinate descent-based LASSO and makes SVM classification much faster (a 2.5x speedup on the yeast UCI dataset).
- 22 Sep 2012 22:33
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.
- 16 Jan 2012 20:45
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.
- 26 Aug 2011 10:49
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.
Heartbeat
- Popularity Score
- 142.69
- Vitality Score
- 11.57
- Subscriptions
- 19
