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r2_score — scikit-learn 1.8.0 documentation
y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 ] >>> r2_score...y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 + 1e-8...scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
Default instance configurations | Elastic Docs
2, 4, 8 4 appsearch Application server, Worker 4 GB 2, 4,...4, 8 2 ccs.default Data, Master, Coordinating 1 GB 1, 2, 4, 8,...www.elastic.co/docs/deploy-manage/deploy/cloud-enterprise/ece-configuring-ece-instance-configurat... -
cross_validation.rst.txt
2, 2, 2, 2] >>> groups = [1, 1, 2, 2, 3, 3, 3] >>>...test)) [2 3] [0 1] [1 3] [0 2] [1 2] [0 3] [0 3] [1 2] [0 2] [1 3]...scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt -
Demo of OPTICS clustering algorithm — scikit-le...
2 ) C3 = [ 1 , - 2 ] + 0.2 * np . random . randn...n_points_per_cluster , 2 ) C4 = [ - 2 , 3 ] + 0.3 * np . random...scikit-learn.org/stable/auto_examples/cluster/plot_optics.html -
model_evaluation.rst.txt
labeling1 = [2, 0, 2, 2, 0, 1] >>> labeling2 = [0, 0, 2, 2, 0, 2] >>>...y_true = [2, 0, 2, 2, 0, 1] >>> y_pred = [0, 0, 2, 2, 0, 2] >>> ...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
SVM Margins Example — scikit-learn 1.8.0 docume...
2 ) - [ 2 , 2 ], np . random . randn ( 20 , 2 ) + [ 2 , 2...This is sqrt(1+a^2) away vertically in # 2-d. margin = 1 / np...scikit-learn.org/stable/auto_examples/svm/plot_svm_margin.html -
classification_report — scikit-learn 1.8.0 docu...
2 , 2 , 2 ] >>> y_pred = [ 0 , 0 , 2 , 2 , 1 ] >>>...sample_weight = None , digits = 2 , output_dict = False , zero_division...scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html -
randomized_svd — scikit-learn 1.8.0 documentation
2), (2,), (2, 4)) On this page This Page...increase this parameter up to 2*k - n_components where k is the...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_svd.html -
L1-based models for Sparse Signals — scikit-lea...
linspace ( - 2 , 2 , n_samples ) freqs = 2 * np . pi * np ....time_step + 2 * ( rng . random_sample () - 0.5 )) X [:, i ] += 0.2 * rng...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
inplace_csr_column_scale — scikit-learn 1...
2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2 , 5...>>> scale = np . array ([ 2 , 3 , 2 ]) >>> csr = sparse...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_csr_column_scale.html