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开源软件名称(OpenSource Name):luispedro/milk开源软件地址(OpenSource Url):https://github.com/luispedro/milk开源编程语言(OpenSource Language):Python 82.3%开源软件介绍(OpenSource Introduction):MILK: MACHINE LEARNING TOOLKITMachine Learning in PythonMilk 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, 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. Milk is flexible about its inputs. It optimised for numpy arrays, but can often handle anything (for example, for SVMs, you can use any dataype and any kernel and it does the right thing). There is a strong emphasis on speed and low memory usage. Therefore, most of the performance sensitive code is in C++. This is behind Python-based interfaces for convenience. To learn more, check the docs at http://packages.python.org/milk/ or the code demos included with the source
at ExamplesHere is how to test how well you can classify some import numpy as np import milk features = np.random.rand(100,10) # 2d array of features: 100 examples of 10 features each labels = np.zeros(100) features[50:] += .5 labels[50:] = 1 confusion_matrix, names = milk.nfoldcrossvalidation(features, labels) print 'Accuracy:', confusion_matrix.trace()/float(confusion_matrix.sum()) If want to use a classifier, you instanciate a learner object and call its
import numpy as np import milk features = np.random.rand(100,10) labels = np.zeros(100) features[50:] += .5 labels[50:] = 1 learner = milk.defaultclassifier() model = learner.train(features, labels) # Now you can use the model on new examples: example = np.random.rand(10) print model.apply(example) example2 = np.random.rand(10) example2 += .5 print model.apply(example2) There are several classification methods in the package, but they all use the
same interface: DetailsLicense: MIT Author: Luis Pedro Coelho (with code from LibSVM and scikits.learn) API Documentation: http://packages.python.org/milk/ Mailing List: http://groups.google.com/group/milk-users Features
Recent HistoryThe ChangeLog file contains a more complete history. New in 0.6.1 (11 May 2015)
New in 0.6 (27 Apr 2015)
New in 0.5.3 (19 Jun 2013)
New in 0.5.2 (7 Mar 2013)
New in 0.5.1 (11 Jan 2013)
New in 0.5 (05 Nov 2012)
For older versions, see |
2023-10-27
2022-08-15
2022-08-17
2022-09-23
2022-08-13
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