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ClassifyI --+ | AbstractClassify --+ | Cosine
The Cosine Classifier uses the cosine distance algorithm to compute the distance between the sample document and each of the specified classes. A cosine classifier needs to be trained with representative examples of each class. From these examples the classifier calculates the most probable classification of the sample. C . S D(C|S) = ------------------------- sqroot(C^2) * sqroot (S^2) Internal data structures: _feature_dectector: holds a feature detector function _classes: holds a list of classes supplied during training _cls_freq_dist: holds a dictionary of Frequency Distributions, this structure is defined in probabilty.py in nltk_lite this structure is indexed by class names and feature types the frequency distributions are indexed by feature values
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Inherited from |
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Train classifier using representative examples of classes; creates frequency distributions of these classes
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