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Lars — scikit-learn 1.8.0 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...n_nonzero_coefs = 500 , eps = np.float64(2.220446049250313e-16) , copy_X...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lars.html -
cluster_optics_dbscan — scikit-learn 1.8....
2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8... ( ... X , ... min_samples = 2 , ... max_eps = np . inf , ......scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_dbscan.html -
indexable — scikit-learn 1.8.0 documentation
2 , 3 ], np . array ([ 2 , 3 , 4 ]), None ,...indexable ( * iterables ) [[1, 2, 3], array([2, 3, 4]), None, <...Sparse...dtype...scikit-learn.org/stable/modules/generated/sklearn.utils.indexable.html -
Comparison of Calibration of Classifiers —...
only 2 are informative, 2 are redundant (random...20 , n_informative = 2 , n_redundant = 2 , random_state = 42 )...scikit-learn.org/stable/auto_examples/calibration/plot_compare_calibration.html -
PowerTransformer — scikit-learn 1.8.0 doc...
2 ], [ 3 , 2 ], [ 4 , 5 ]] >>>...0 and lambda_ != 2 : X_original = 1 - ( - ( 2 - lambda_ ) * X...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
Face completion with a multi-output estimators ...
n_pixels // 2 :] X_test = test [:, : ( n_pixels + 1 ) // 2 ] y_test.... figure ( figsize = ( 2.0 * n_cols , 2.26 * n_faces )) plt ....scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.html -
contingency_matrix — scikit-learn 1.8.0 d...
2 , 2 ] >>> labels_pred = [ 1 , 0 , 2 , 1 , 0...0 , 2 ] >>> contingency_matrix ( labels_true , labels_pred...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.contingency_matrix.html -
Plotting Learning Curves and Checking Models’ S...
subplots ( nrows = 2 , ncols = 2 , figsize = ( 16 , 12 ),...subplots ( nrows = 1 , ncols = 2 , figsize = ( 10 , 6 ), sharey...scikit-learn.org/stable/auto_examples/model_selection/plot_learning_curve.html -
mean_pinball_loss — scikit-learn 1.8.0 do...
2 , 3 ] >>> mean_pinball_loss...mean_pinball_loss ( y_true , [ 0 , 2 , 3 ], alpha = 0.1 ) 0.03... >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html -
ARIMA models in Python
987 Model: SARIMAX(2, 1, 1)x(2, 0, [1, 2], 12) Log Likelihood...the model is SARIMAX(2, 1, 1)x(2, 0, [1, 2], 12) , which means...developer.ibm.com/tutorials/awb-arima-models-in-python/