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CategoricalNB — scikit-learn 1.6.1 documentation
alpha = 1.0 , force_alpha = True , fit_prior = True , class_prior...class_prior = None , min_categories = None ) [source] # Naive Bayes...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.CategoricalNB.html -
RFE — scikit-learn 1.6.1 documentation
n_features_to_select = None , step = 1 , verbose = 0 , importance_getter = 'auto'...X , y = make_friedman1 ( n_samples = 50 , n_features = 10 , random_state...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFE.html -
plot_classifier_comparison.rst.txt
py: ========== Classifier comparison ========== A comparison...random_state=42), SVC(gamma=2, C=1, random_state=42), GaussianProcessClass(1.0...scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt -
PredefinedSplit — scikit-learn 1.6.1 documentation
Train: index=[1 2 3] Test: index=[0] Fold 1: Train: index=[0 2] Test:...get_n_splits ( X = None , y = None , groups = None ) [source]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.PredefinedSplit.html -
Comparison of F-test and mutual information — s...
fontsize = 14 ) if i == 0 : plt . ylabel ( "$y$" , fontsize = 14 )...seed ( 0 ) X = np . random . rand ( 1000 , 3 ) y = X [:, 0 ] +...scikit-learn.org/stable/auto_examples/feature_selection/plot_f_test_vs_mi.html -
Nearest Centroid Classification — scikit-learn ...
c = y , cmap = cmap_bold , edgecolor = "k" , s = 20 ) plt...shrinkage , np . mean ( y == y_pred )) _ , ax = plt . subplots () DecisionBoundaryDisp...scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html -
One-class SVM with non-linear kernel (RBF) — sc...
X_outliers = np . random . uniform ( low =- 4 , high = 4 , size = ( 20...levels = [ 0 ], colors = "darkred" , linewidths = 2 , ) s = 40 b1...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html -
documentMap (documentDefinitionMap) | DBFlute
propertiesHtmlMap = map: { ; df:header = map:{ ; title = [title of PropertiesHTML]...loadDataReverseMap = map: { ; recordLimit = [limit size] # デフォルト:...dbflute.seasar.org/ja/manual/reference/dfprop/documentdefinition/index.html -
top_k_accuracy_score — scikit-learn 1.6.1 docum...
normalize == True and the number of samples with normalize == False...y_score , * , k = 2 , normalize = True , sample_weight = None , labels...scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html -
Bisecting K-Means and Regular K-Means Performan...
data n_samples = 10000 random_state = 0 X , _ = make_blobs ( n_samples...n_samples = n_samples , centers = 2 , random_state = random_state...scikit-learn.org/stable/auto_examples/cluster/plot_bisect_kmeans.html