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Milk 0.4.0 releases the Python machine learning kit

Source: Internet
Author: User
Keywords Machine learning Python milk
Tags based codes different economy error example learning processing
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Milk is a machine learning kit in Python. Its focus is to provide supervised classifications and several effective classification analyses: SVMs (based on LIBSVM), nn, stochastic forest economy and decision tree. It also performs feature selection. These classifications can be combined in many ways to form different classification systems. For unsupervised learning, milk supports K clustering and affinity propagation.

Milk 0.4.0 new features: Parallel processing, perceptron and error-correcting output codes. Enhancements: Setting up random seeds in a stochastic forest economy, Defaultlearner () adds the "multi_strategy" parameter, the return value is Gridminimise, and the faster network kernel supports SVMS and S-shape fitting. A randomforest error was corrected.

Example：

Import&http://www.aliyun.com/zixun/aggregation/37954.html ">nbsp;numpy as NP import milk features = Np.random.rand ( 100,10) labels = Np.zeros (m) features[50:] = = 5 Labels[50:] = 1 learner = Milk.defaultclassifier () model = Learner.train (  features, labels) # Now I can use the model on new examples:example = Np.random.rand Print model.apply (example) example2 = Np.random.rand (example2 = 5 print model.apply (example2)

Download Address: milk-0.4.0.tar.gz (MD5)

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Related Keywords:
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