milk is a Machine Learning toolkit written in Python. Its focus is on supervised classification.
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Here are some key features of "milk":
· SVMs. Using the libsvm solver with a pythonesque wrapper around it
· Stepwise Discriminant Analysis for feature selection
Requirements:
· Python
What's New in This Release: [ read full changelog ]
· Make defaultlearner able to take extra arguments
· Make ctransforms_model a supervised_model (adds apply_many)
· Add expanded argument to defaultlearner
· Fix corner case in SDA
· Fix repeated_kmeans
· Fix parallel gridminimise on Windows
· Add multi_label argument to normaliselabels
· Add multi_label argument to nfoldcrossvalidation.foldgenerator
· Do not fork a process in gridminimise if nprocs == 1 (makes for easier debugging, at the cost of slightly more complex code).
· Add milk.supervised.multi_label
· Fix ext.jugparallel when features is a Task
· Add milk.measures.bayesian_significance
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