Package nltk :: Package classify :: Module maxent :: Class FunctionBackedMaxentFeatureEncoding

Class FunctionBackedMaxentFeatureEncoding

            object --+    
                     |    
MaxentFeatureEncodingI --+
                         |
                        FunctionBackedMaxentFeatureEncoding

A feature encoding that calls a user-supplied function to map a given featureset/label pair to a sparse joint-feature vector.

Instance Methods

[hide private]

__init__(self, func, length, labels)
Construct a new feature encoding based on the given function.

source code

list of (int, number)

encode(self, featureset, label)
Given a (featureset, label) pair, return the corresponding vector of joint-feature values.

source code

int

length(self)
Returns: The size of the fixed-length joint-feature vectors that are generated by this encoding.

source code

list

labels(self)
Returns: 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. source code

str

describe(self, fid)
Returns: A string describing the value of the joint-feature whose index in the generated feature vectors is fid. source code

Inherited from MaxentFeatureEncodingI: train

Inherited from object: __delattr__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __str__

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

init(self, func, length, labels)
(Constructor)

source code

Construct a new feature encoding based on the given function.

Parameters:

func ((callable)) - A function that takes two arguments, a featureset and a label, and returns the sparse joint feature vector that encodes them:
```
>>> func(featureset, label) -> feature_vector
```
This sparse joint feature vector (feature_vector) is a list of (index,value) tuples.
length (int) - The size of the fixed-length joint-feature vectors that are generated by this encoding.
labels (list) - A list of the "known labels" for this encoding -- i.e., all labels l such that self.encode(fs,l) can be a nonzero joint-feature vector for some value of fs.

Overrides: object.__init__

encode(self, featureset, label)

source code

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)

length(self)

source code

Returns: int: The size of the fixed-length joint-feature vectors that are generated by this encoding.
Overrides: MaxentFeatureEncodingI.length: (inherited documentation)

labels(self)

source code

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)

describe(self, fid)

source code

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)

Class FunctionBackedMaxentFeatureEncoding

__init__(self, func, length, labels) (Constructor)

encode(self, featureset, label)

length(self)

labels(self)

describe(self, fid)

init(self, func, length, labels)
(Constructor)