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Gradient Boosting Out-of-Bag estimates — scikit...
n_splits = None ): cv = KFold ( n_splits = n_splits ) cv_clf = ensemble...) x1 = random_state . uniform ( size = n_samples ) x2 = random_state...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html -
Understanding the decision tree structure — sci...
iris = load_iris () X = iris . data y = iris . target...y_test = train_test_split ( X , y , random_state = 0 ) clf = DecisionTreeClassifi...scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html -
alter-step1-prepare.png
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alter-step2-open.png
17639795 width=1416, height=610, bitDepth=8, colorType=RGBAlpha, ...translatedKeyword=, text=<x:xmpmeta xmlns:x="adobe:ns:meta/" x:xmptk="XMP...dbflute.seasar.org/data/snapshot/intro/alter/alter-step2-open.png -
Multiclass Receiver Operating Characteristic (R...
pair_list ): a_mask = y_test == label_a b_mask = y_test == label_b ab_mask...color = color , ax = ax , plot_chance_level = ( class_id == 2 ),...scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html -
Two-class AdaBoost — scikit-learn 1.5.0 documen...
[ y == i ], bins = 10 , range = plot_range , facecolor = c ,...n_features = 2 , n_classes = 2 , random_state = 1 ) X2 , y2 = make_gaussian_quantiles...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html -
Receiver Operating Characteristic (ROC) with cr...
random_state = random_state ) tprs = [] aucs = [] mean_fpr = np . linspace...name = f "ROC fold { fold } " , alpha = 0.3 , lw = 1 , ax = ax...scikit-learn.org/stable/auto_examples/model_selection/plot_roc_crossval.html -
intro-operate-linkdoc-snapshot.png
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friends-Eclipse-CodeFormatter-settings-save-act...
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lastaflute-swagger-ui-basic-snapshot.png
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