type TadmEventMaxentFeatureEncoding

Parameters:

• labels - A list of the "known labels" for this encoding.
• mapping - A dictionary mapping from (fname,fval,label) tuples to corresponding joint-feature indexes. These indexes must be the set of integers from 0...len(mapping). If mapping[fname,fval,label]=id, then self.encode({..., fname:fval, ...}, label)[id] is 1; otherwise, it is 0.
• unseen_features - If true, then include unseen value features in the generated joint-feature vectors.
• alwayson_features - If true, then include always-on features in the generated joint-feature vectors.

Overrides: BinaryMaxentFeatureEncoding.__init__

(inherited documentation)

Given a (featureset, label) pair, return the corresponding vector of joint-feature values. This vector is represented as a list of (index, value) tuples, specifying the value of each non-zero joint-feature.

Returns: list of (int, number)

Overrides: MaxentFeatureEncodingI.encode

(inherited documentation)

Returns: list

A list of the "known labels" -- i.e., all labels l such that self.encode(fs,l) can be a nonzero joint-feature vector for some value of fs.

Overrides: MaxentFeatureEncodingI.labels

(inherited documentation)

Returns: str

A string describing the value of the joint-feature whose index in the generated feature vectors is fid.

Overrides: MaxentFeatureEncodingI.describe

(inherited documentation)

Returns: int

The size of the fixed-length joint-feature vectors that are generated by this encoding.

Overrides: MaxentFeatureEncodingI.length

(inherited documentation)

Construct and return new feature encoding, based on a given training corpus train_toks. See the class description for a description of the joint-features that will be included in this encoding.

Parameters:

• train_toks - Training data, represented as a list of pairs, the first member of which is a feature dictionary, and the second of which is a classification label.
• count_cutoff - A cutoff value that is used to discard rare joint-features. If a joint-feature's value is 1 fewer than count_cutoff times in the training corpus, then that joint-feature is not included in the generated encoding.
• labels - A list of labels that should be used by the classifier. If not specified, then the set of labels attested in train_toks will be used.
• options - Extra parameters for the constructor, such as unseen_features and alwayson_features.

Overrides: MaxentFeatureEncodingI.train

(inherited documentation)