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QuantileRegressor — scikit-learn 1.7.0 document...
quantile = 0.5 , alpha = 1.0 , fit_intercept = True , solver = 'highs'...n_samples , n_features = 10 , 2 >>> rng = np . random . RandomState...scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html -
CategoricalNB — scikit-learn 1.7.0 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 -
Matern — scikit-learn 1.7.0 documentation
length_scale = 1.0 , length_scale_bounds = (1e-05, 100000.0) , nu = 1.5...>>> X , y = load_iris ( return_X_y = True ) >>> kernel = 1.0 * Matern...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Matern.html -
Probabilistic predictions with Gaussian process...
train_size = 50 rng = np . random . RandomState ( 0 ) X = rng . uniform...train_size ], c = "k" , label = "Train data" , edgecolors = ( 0 , 0 ,...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc.html -
Developing scikit-learn estimators — scikit-lea...
method: clf2 = SGDClassifier ( alpha = 2.3 ) clf3 = SGDClassifier...self , param1 = 1 , param2 = 2 ): self . param1 = param1 self ....scikit-learn.org/stable/developers/develop.html -
RFE — scikit-learn 1.7.0 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 -
set_config — scikit-learn 1.7.0 documentation
assume_finite = None , working_memory = None , print_changed_only = None...None , display = None , pairwise_dist_chunk_size = None , enabl...scikit-learn.org/stable/modules/generated/sklearn.set_config.html -
Principal Component Analysis (PCA) on Iris Data...
projection = "3d" , elev =- 150 , azim = 110 ) X_reduced = PCA ( n_components...PCA fig = plt . figure ( 1 , figsize = ( 8 , 6 )) ax = fig . add_subplot...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_iris.html -
Ridge coefficients as a function of the L2 Regu...
w = make_regression ( n_samples = 100 , n_features = 10 ,...n_informative = 8 , coef = True , random_state = 1 ) # Obtain...scikit-learn.org/stable/auto_examples/linear_model/plot_ridge_coeffs.html -
RationalQuadratic — scikit-learn 1.7.0 document...
length_scale = 1.0 , alpha = 1.0 , length_scale_bounds = (1e-05, 100000.0)...>>> X , y = load_iris ( return_X_y = True ) >>> kernel = RationalQuadratic...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RationalQuadratic.html