Of(2SSKJrJr SSKJr "SS\S9rg))ABCMetaabstractmethod)DictionaryProbDistcd\rSrSrSr\S Sj5r\S5rSrSr \S5r Sr S r S r g ) ClusterIz4 Interface covering basic clustering functionality. cg)z Assigns the vectors to clusters, learning the clustering parameters from the data. Returns a cluster identifier for each vector. N)selfvectorsassign_clusterss 2/usr/lib/python3/dist-packages/nltk/cluster/api.pyclusterClusterI.clustercg)zh Classifies the token into a cluster, setting the token's CLUSTER parameter to that cluster identifier. Nr )r tokens rclassifyClusterI.classifyrrc0URU5U:Xagg)zQ Returns the likelihood (a float) of the token having the corresponding cluster. g?)r)r vectorlabels r likelihoodClusterI.likelihood!s == E )rc0nSnUR5HnURX5X$'X2U- nM UR5HnX$==U-ss'M [U5$)zi Classifies the token into a cluster, returning a probability distribution over the cluster identifiers. r) cluster_namesrr)r r likelihoodssumrs rclassification_probdist ClusterI.classification_probdist+sm  ))+G#'??6#CK w' 'C,))+G  C ' ,!+..rcg)z! Returns the number of clusters. Nr r s r num_clustersClusterI.num_clusters9rrcF[[UR555$)z1 Returns the names of the clusters. :rtype: list )listranger%r$s rrClusterI.cluster_names?s E$++-.//rcU$)z, Returns the names of the cluster at index. r )r indexs r cluster_nameClusterI.cluster_nameFs  rr N)F)__name__ __module__ __qualname____firstlineno____doc__rrrrr!r%rr-__static_attributes__r rrrrsW     /  0rr) metaclassN)abcrrnltk.probabilityrrr rrr8s(/<<r