ó ê-iz ãóN•SrSSKrSSKJr SSKJr SSKJrJ r "SS\5r g) zY Feature agglomeration. Base classes and functions for performing feature agglomeration. éN)Úissparseé)ÚTransformerMixin)Úcheck_is_fittedÚ validate_datacó$•\rSrSrSrSrSrSrg)ÚAgglomerationTransforméz@ A class for feature agglomeration via the transform interface. c ó–•[U5 [XSS9nUR[R:Xa™[ U5(d‰[R "UR5nURSn[R"[U5Vs/sH-n[R "URXSS245U- PM/ sn5nU$[R"UR5Vs/sH'nURUSS2URU:H4SS9PM) nn[R"U5RnU$s snfs snf)a” Transform a new matrix using the built clustering. Parameters ---------- X : array-like of shape (n_samples, n_features) or (n_samples, n_samples) A M by N array of M observations in N dimensions or a length M array of M one-dimensional observations. Returns ------- Y : ndarray of shape (n_samples, n_clusters) or (n_clusters,) The pooled values for each feature cluster. F)ÚresetrNé)Úaxis) rrÚ pooling_funcÚnpÚmeanrÚbincountÚlabels_ÚshapeÚarrayÚrangeÚuniqueÚT)ÚselfÚXÚsizeÚ n_samplesÚiÚnXÚls ÚY/var/www/html/venv/lib/python3.13/site-packages/sklearn/cluster/_feature_agglomeration.pyÚ transformÚ AgglomerationTransform.transforms€ô ˜Ôä ˜$¨Ñ /ˆØ × Ñ ¤§¡Ó '´¸· ± Ü—;’;˜tŸ|™|Ó,ˆDØŸ™ ™ ˆIä—’ÜDIÈ)ÔDTÓUÒDT¸q”—’˜TŸ\™\¨1²¨T©7Ó3°dÔ:ÑDTÑUóˆBðˆ ôŸš 4§<¡<Ô0óâ0Að×!Ñ! !¢A t§|¡|°qÑ'8Ð$8Ñ"9ÀÐ!ÓBÙ0ð ðô—’˜"“—‘ˆB؈ ùòVùòs Â4EÃ/.Ecóh•[U5 [R"URSS9up#USU4$)a˜ Inverse the transformation and return a vector of size `n_features`. Parameters ---------- X : array-like of shape (n_samples, n_clusters) or (n_clusters,) The values to be assigned to each cluster of samples. Returns ------- X_original : ndarray of shape (n_samples, n_features) or (n_features,) A vector of size `n_samples` with the values of `X` assigned to each of the cluster of samples. T)Úreturn_inverse.)rrrr)rrÚunilÚinverses r Úinverse_transformÚ(AgglomerationTransform.inverse_transform:s0€ô ˜ÔäŸ š  $§,¡,¸tÑD‰ ˆØg‰Ðó©N)Ú__name__Ú __module__Ú __qualname__Ú__firstlineno__Ú__doc__r!r'Ú__static_attributes__r*r)r r r s†ñò õDr)r ) r/ÚnumpyrÚ scipy.sparserÚbaserÚutils.validationrrr r*r)r Úr5s%ðñóÝ!å#ß=ô 9Ð-õ9r)