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Description du projet

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.

Système requise

System requirement is not defined
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2011-08-25 06:52 Retour à la liste release
0.4.0

Nouvelles fonctionnalités: le traitement parallèle, perceptron, et codes correcteurs d'erreurs de sortie. Améliorations: mise la graine aléatoire dans les forêts aléatoires, un «multi_strategy« paramètre pour defaultlearner (), une valeur de retour de gridminimise, plus rapide point-kernel SVMs, et l'ajustement sigmoïde. Un bugfix dans randomforest.
Tags: Major
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.

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