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| Package nltk_lite :: Package cluster :: Class VectorSpace |
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ClusterI --+
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VectorSpace
EM,
GroupAverageAgglomerative,
KMeans| Method Summary | |
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classify(self,
vector)
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Returns the index of the appropriate cluster for the vector. | |
Assigns the vectors to clusters, learning the clustering parameters from the data. | |
Finds the clusters using the given set of vectors. | |
Returns the likelihood (a float) of the token having the corresponding cluster. | |
Returns the likelihood of the vector belonging to the cluster. | |
Returns the vector after normalisation and dimensionality reduction | |
Normalises the vector to unit length. | |
Inherited from ClusterI:
classification_probdist,
cluster_name,
cluster_names,
num_clusters
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| Method Details |
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__init__(self,
normalise=False,
svd_dimensions=None)
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classify_vectorspace(self, vector)Returns the index of the appropriate cluster for the vector. |
cluster(self, vectors, assign_clusters=False, trace=False)Assigns the vectors to clusters, learning the clustering parameters from the data. Returns a cluster identifier for each vector.
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cluster_vectorspace(self, vectors, trace)Finds the clusters using the given set of vectors. |
likelihood(self, vector, label)Returns the likelihood (a float) of the token having the corresponding cluster.
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likelihood_vectorspace(self, vector, cluster)Returns the likelihood of the vector belonging to the cluster. |
vector(self, vector)Returns the vector after normalisation and dimensionality reduction |
_normalise(self, vector)Normalises the vector to unit length. |
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