+ h(:^RIHtHt^RIHt!RR]R7tR#))ABCMetaabstractmethod)DictionaryProbDistcpa]tRt^toRt]R Rl4t]R4tRtRt ]R4t Rt Rt R t VtR #) ClusterIz4 Interface covering basic clustering functionality. c R#)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.clusterc R#)zh Classifies the token into a cluster, setting the token's CLUSTER parameter to that cluster identifier. Nr )r tokens&&r classifyClusterI.classifyrrc 6VPV4V8XdR#R#)zQ Returns the likelihood (a float) of the token having the corresponding cluster. g?)r)r vectorlabels&&&r likelihoodClusterI.likelihood!s == E )rc /pRpVP4F%pVPW4W$&W2V,, pK' VP4FpW$;;,V,uu&K \V4#)zi Classifies the token into a cluster, returning a probability distribution over the cluster identifiers. r) cluster_namesrr)r r likelihoodssumrs&& r classification_probdist ClusterI.classification_probdist+sm  ))+G#'??6#CK w' 'C,))+G  C ' ,!+..rc R#)z! Returns the number of clusters. Nr r s&r num_clustersClusterI.num_clusters9rrc F\\VP444#)z1 Returns the names of the clusters. :rtype: list )listranger$r#s&r rClusterI.cluster_names?s E$++-.//rc V#)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____classdictcell__) __classdict__s@r rrs_     /  0rr) metaclassN)abcrrnltk.probabilityrrr rr r9s(/<<r