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theme.min.css
1 3.6-8.1 8.1s3.6 8.1 8.1 8.1 8.1-3.6 8.1-8.1-3.6-8.1-8.1-8.1zM2.5...0-8.1 3.6-8.1 8.1s3.6 8.1 8.1 8.1 8.1-3.6 8.1-8.1-3.6-8.1-8.1-8.1zM2.5...fess.codelibs.org/_static/assets/css/theme.min.css -
dict-19.png
alpha=8 RGB 8 8 8 8 5271 1 1.0 1 8 8 8 8 true true 1015 Normal...fess.codelibs.org/ja/_images/dict-19.png -
Fess Configuration Properties
1,2,4:2,5:1 file.role.from.file Enable...as String[]).fileConfigIds([{1}] as String[]).dataConfigIds([{2}]...fess.codelibs.org/14.19/config/properties.html -
Searching complex documents with ColPali - part...
documents with ColPali - part 1 The article introduces the ColPali...https://arxiv.org/pdf/2407.01449 Figure 1 Let’s first take a look at how...www.elastic.co/search-labs/blog/elastiacsearch-colpali-document-search -
3 U.S. soldiers found dead in Lithuania; 1 stil...
The bodies of three U.S.www.nbcnews.com/news/military/3-us-soldiers-found-dead-lithuania-1-still-missing-vehicle-swallowe... -
1.4. Support Vector Machines — scikit-learn 1.6...
“0 vs 1”, “0 vs 2” , … “0 vs n”, “1 vs 2”, “1 vs 3”, “1 vs n”,...vectors \(v^{0}_1, v^{1}_1\) and \(v^{0}_2, v^{1}_2\) respectively....scikit-learn.org/stable/modules/svm.html -
TimeSeriesSplit — scikit-learn 1.6.1 documentation
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [...index=[0] Test: index=[1] Fold 1: Train: index=[0 1] Test: index=[2]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html -
LocalOutlierFactor — scikit-learn 1.6.1 documen...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...fit_predict ( X ) array([ 1, 1, -1, 1]) >>> clf . negative_outlier_factor_...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html -
ShuffleSplit — scikit-learn 1.6.1 documentation
array ([ 1 , 2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Train: index=[1 3 0 4] Test: index=[5 2] Fold 1: Train: index=[4...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
SparseCoder — scikit-learn 1.6.1 documentation
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>> dictionary...scikit-learn.org/stable/modules/generated/sklearn.decomposition.SparseCoder.html
