.. _example_bicluster_bicluster_newsgroups.py: ================================================================ Biclustering documents with the Spectral Co-clustering algorithm ================================================================ This example demonstrates the Spectral Co-clustering algorithm on the twenty newsgroups dataset. The 'comp.os.ms-windows.misc' category is excluded because it contains many posts containing nothing but data. The TF-IDF vectorized posts form a word frequency matrix, which is then biclustered using Dhillon's Spectral Co-Clustering algorithm. The resulting document-word biclusters indicate subsets words used more often in those subsets documents. For a few of the best biclusters, its most common document categories and its ten most important words get printed. The best biclusters are determined by their normalized cut. The best words are determined by comparing their sums inside and outside the bicluster. For comparison, the documents are also clustered using MiniBatchKMeans. The document clusters derived from the biclusters achieve a better V-measure than clusters found by MiniBatchKMeans. Output:: Vectorizing... Coclustering... Done in 9.53s. V-measure: 0.4455 MiniBatchKMeans... Done in 12.00s. V-measure: 0.3309 Best biclusters: ---------------- bicluster 0 : 1951 documents, 4373 words categories : 23% talk.politics.guns, 19% talk.politics.misc, 14% sci.med words : gun, guns, geb, banks, firearms, drugs, gordon, clinton, cdt, amendment bicluster 1 : 1165 documents, 3304 words categories : 29% talk.politics.mideast, 26% soc.religion.christian, 25% alt.atheism words : god, jesus, christians, atheists, kent, sin, morality, belief, resurrection, marriage bicluster 2 : 2219 documents, 2830 words categories : 18% comp.sys.mac.hardware, 16% comp.sys.ibm.pc.hardware, 16% comp.graphics words : voltage, dsp, board, receiver, circuit, shipping, packages, stereo, compression, package bicluster 3 : 1860 documents, 2745 words categories : 26% rec.motorcycles, 23% rec.autos, 13% misc.forsale words : bike, car, dod, engine, motorcycle, ride, honda, cars, bmw, bikes bicluster 4 : 12 documents, 155 words categories : 100% rec.sport.hockey words : scorer, unassisted, reichel, semak, sweeney, kovalenko, ricci, audette, momesso, nedved **Python source code:** :download:`bicluster_newsgroups.py ` .. literalinclude:: bicluster_newsgroups.py :lines: 55-