__init__ (encoding, weights[, logarithmic]) |
Construct a new maxent classifier model. |
classify (featureset) |
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classify_many (featuresets) |
Apply self.classify() to each element of featuresets . |
explain (featureset[, columns]) |
Print a table showing the effect of each of the features in the given feature set, and how they combine to determine the probabilities of each label for that featureset. |
labels () |
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prob_classify (featureset) |
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prob_classify_many (featuresets) |
Apply self.prob_classify() to each element of featuresets . |
set_weights (new_weights) |
Set the feature weight vector for this classifier. |
show_most_informative_features ([n, show]) |
param show: | all, neg, or pos (for negative-only or positive-only) |
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train (train_toks[, algorithm, trace, ...]) |
Train a new maxent classifier based on the given corpus of training samples. |
unicode_repr () |
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weights () |
return: | The feature weight vector for this classifier. |
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