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Probability calibration of classifiers — scikit...
): this_X = X_train [ y_train == this_y ] this_sw = sw_train [...n_samples = n_samples , centers = centers , shuffle = False , random_state...scikit-learn.org/stable/auto_examples/calibration/plot_calibration.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 -
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 -
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35273367 width=64, height=64, bitDepth=8, colorType=RGBAlpha, c...whitePointX=31270, whitePointY=32900, redX=64000, redY=33000, greenX=30000,...www.elastic.co/favicon_64x64_16bit.png -
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 -
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 -
ElasticNetCV — scikit-learn 1.7.0 documentation
max_iter = 1000 , tol = 0.0001 , cv = None , copy_X = True , verbose...l1_ratio = 0.5 , eps = 0.001 , n_alphas = 100 , alphas = None ,...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNetCV.html -
Demonstration of k-means assumptions — scikit-l...
( X [ y == 0 ][: 500 ], X [ y == 1 ][: 100 ], X [ y == 2 ][: 10...axs = plt . subplots ( nrows = 2 , ncols = 2 , figsize = ( 12...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html -
IsotonicRegression — scikit-learn 1.7.0 documen...
y_min = None , y_max = None , increasing = True , out_of_bounds...X , y = make_regression ( n_samples = 10 , n_features = 1 , random_state...scikit-learn.org/stable/modules/generated/sklearn.isotonic.IsotonicRegression.html -
Plotting Cross-Validated Predictions — scikit-l...
y = load_diabetes ( return_X_y = True ) lr = LinearRegression...y_pred = cross_val_predict ( lr , X , y , cv = 10 ) Since cv=10 ,...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html
