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Generalized Linear Models — scikit-learn 1.8.0 ...
Examples concerning the sklearn.linear_model module. Comparing Linear Bayesian Regressors Curve Fitting with Bayesian Ridge Regression Decision Boundaries of Multinomial and One-vs-Rest Logistic Re...scikit-learn.org/stable/auto_examples/linear_model/index.html -
__sklearn_is_fitted__ as Developer API — scikit...
scikit-learn 1.6 Release Highlights for scikit-learn 1.6 Gallery...__init__ ( self , parameter = 1 ): self . parameter = parameter...scikit-learn.org/stable/auto_examples/developing_estimators/sklearn_is_fitted.html -
Monotonic Constraints — scikit-learn 1.8.0 docu...
normal ( loc = 0.0 , scale = 0.01 , size = n_samples )...`interaction_cst=[{0, 1}]` is equivalent to `interaction_cst=[{0, 1}, {2,...scikit-learn.org/stable/auto_examples/ensemble/plot_monotonic_constraints.html -
Decision Trees — scikit-learn 1.8.0 documentation
Examples concerning the sklearn.tree module. Decision Tree Regression Plot the decision surface of decision trees trained on the iris dataset Post pruning decision trees with cost complexity prunin...scikit-learn.org/stable/auto_examples/tree/index.html -
Dataset examples — scikit-learn 1.8.0 documenta...
Examples concerning the sklearn.datasets module. Plot randomly generated multilabel datasetscikit-learn.org/stable/auto_examples/datasets/index.html -
Plot randomly generated multilabel dataset — sc...
red 0.52 0.46 0.54 blue 0.28 0.59 0.41 yellow 0.19 0.50 0.50 #..." %s \t %0.2f \t %0.2f \t %0.2f " % ( k , p , p_w [ 0 ], p_w [...scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html -
Visualizing the stock market structure — scikit...
axes ([ 0.0 , 0.0 , 1.0 , 1.0 ]) plt . axis ( "off"...ay([ 0.03162278, 0.05994843, 0.11364637, 0.21544347, 0.40842387,...scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html -
Gaussian processes on discrete data structures ...
array ([ 1.0 , 1.0 , 2.0 , 2.0 , 3.0 , 3.0 ]) training_idx...)), [ 1.0 if c else - 1.0 for c in Y_train ], s = 100 , marker...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html -
Gradient Boosting regression — scikit-learn 1.8...
subplot ( 1 , 1 , 1 ) plt . title ( "Deviance"...train_test_split ( X , y , test_size = 0.1 , random_state = 13 ) params...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html -
Probabilistic predictions with Gaussian process...
Accuracy: 1.000 (initial) 1.000 (optimized) Log-loss: 0.214 (initial)...edgecolors = ( 0 , 0 , 0 ) ) X_ = np . linspace ( 0 , 5 , 100 ) plt ....scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc.html