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项目描述

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.

系统要求

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2010-12-18 07:17 Back to release list
0.3.6

新功能:无监督(1级)核密度模型,一重选择一些学习者,学习者树桩,与Adaboost。一种修正当SDA返回空。
标签: Minor, bugfix
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.

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