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專案描述

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.

System Requirements

System requirement is not defined
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2011-02-11 01:21
0.3.7

Logistic regression was added. Demos are included in the source and documentation. Cluster agreement metrics were added. An nfoldcrossvalidation bug when using the origins parameter was fixed.
標籤: Minor, bugfix

2010-12-18 07:17
0.3.6

New features: unsupervised (1-class) kernel density modeling, a weights option to some learners, stump learner, and Adaboost. A fix for when SDA returns empty.
標籤: Minor, bugfix

2010-11-04 16:07
0.3.5

A fix was included for 64-bit machines. Functions in measures.py have a new interface.
標籤: Minor, Minor bugfixes

2010-11-01 18:34
0.3.4

Random forest learners were added. Decision trees were sped up by 20 times. Gridsearch is much faster since it finds an optimum without computing all folds.
標籤: Stable, Minor

2010-10-23 14:46
0.3.3

A missing file that prevented installation was included.
標籤: Stable, Minor

Project Resources