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Slashdot: News for nerds, stuff that matters
whole WORLD in a mud puddle! -- Doug Clifford Close Working......debates -- sometimes over a single word -- stalled agreement on key...science.slashdot.org -
Biclustering documents with the Spectral Co-clu...
out_of_cluster_docs )[ 0 ] word_col = X [:, cluster_words ] word_scores = np...) ) word_scores = word_scores . ravel () important_words = list...scikit-learn.org/stable/auto_examples/bicluster/plot_bicluster_newsgroups.html -
MetaFilter | Community Weblog
" the world's very first work of interactive fiction....Windows 95, the RTF-compatabile word processor Microsoft WordPad...www.metafilter.com/ -
1.5. Stochastic Gradient Descent — scikit-learn...
word frequencies or indicator features)...We found that Averaged SGD works best with a larger number of...scikit-learn.org/stable/modules/sgd.html -
Elastic Advances LLM Security with Standardized...
word and sensitive information filters...Elastic. The initial ONWeek work undertaken by the team involved...www.elastic.co/security-labs/elastic-advances-llm-security -
FeatureHasher and DictVectorizer Comparison — s...
functions # A token may be a word, part of a word or anything comprised...between the words in a sentence is often called a Bag of Words representation...scikit-learn.org/stable/auto_examples/text/plot_hashing_vs_dict_vectorizer.html -
Classification of text documents using sparse f...
documents by topics using a Bag of Words approach . This example uses...max_df = 0.5 , min_df = 5 , stop_words = "english" ) X_train = vectorizer...scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html -
Topic extraction with Non-negative Matrix Facto...
plot_top_words ( model , feature_names , n_top_words , title ):...replies, and common English words, words occurring in # only one...scikit-learn.org/stable/auto_examples/applications/plot_topics_extraction_with_nmf_lda.html -
Clustering text documents using k-means — sciki...
frequent words to features indices and hence compute a word occurrence...documents by topics using a Bag of Words approach . Two algorithms are...scikit-learn.org/stable/auto_examples/text/plot_document_clustering.html -
auto_examples_python.zip
er_docs)[0] word_col = X[:, cluster_words] word_scores = np.array(...:].sum(axis=0) ) word_scores = word_scores.ravel() important_words = list(...scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip