`nltk.cluster.VectorSpaceClusterer`¶

class nltk.cluster.VectorSpaceClusterer(normalise=False, svd_dimensions=None)[source]¶: Abstract clusterer which takes tokens and maps them into a vector space. Optionally performs singular value decomposition to reduce the dimensionality.

Methods¶

__init__([normalise, svd_dimensions])

param normalise:
	should vectors be normalised to length 1

classification_probdist(vector) Classifies the token into a cluster, returning a probability distribution over the cluster identifiers.

classify(vector)

classify_vectorspace(vector) Returns the index of the appropriate cluster for the vector.

cluster(vectors[, assign_clusters, trace])

cluster_name(index) Returns the names of the cluster at index.

cluster_names() Returns the names of the clusters.

cluster_vectorspace(vectors, trace) Finds the clusters using the given set of vectors.

likelihood(vector, label)

likelihood_vectorspace(vector, cluster) Returns the likelihood of the vector belonging to the cluster.

num_clusters() Returns the number of clusters.

vector(vector) Returns the vector after normalisation and dimensionality reduction