Abstract clusterer which takes tokens and maps them into a vector
space. Optionally performs singular value decomposition to reduce the
dimensionality.
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cluster(self,
vectors,
assign_clusters=False,
trace=False)
Assigns the vectors to clusters, learning the clustering parameters
from the data. |
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cluster_vectorspace(self,
vectors,
trace)
Finds the clusters using the given set of vectors. |
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classify(self,
vector)
Classifies the token into a cluster, setting the token's CLUSTER
parameter to that cluster identifier. |
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classify_vectorspace(self,
vector)
Returns the index of the appropriate cluster for the vector. |
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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. |
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vector(self,
vector)
Returns the vector after normalisation and dimensionality reduction |
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_normalise(self,
vector)
Normalises the vector to unit length. |
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Inherited from api.ClusterI:
classification_probdist,
cluster_name,
cluster_names,
num_clusters
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