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Projeto Descrição

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.

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2011-08-25 06:52 Back to release list
0.4.0

Novos recursos: processamento paralelo, perceptron, erro e corrigir códigos de saída. Melhorias: definição da semente aleatória em florestas aleatórias, uma "multi_strategy 'parâmetro para defaultlearner (), um valor de retorno de gridminimise, mais rápido dot kernel-SVMs e montagem sigmoidal. Um bugfix em 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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