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A demo of the Spectral Co-Clustering algorithm ...
consensus score: 1.000 # Authors: The scikit-learn...permutation ( data . shape [ 1 ]) data = data [ row_idx ][:,...scikit-learn.org/stable/auto_examples/bicluster/plot_spectral_coclustering.html -
Tweedie regression on insurance claims — ...
tweedie_powers = [ 1.5 , 1.7 , 1.8 , 1.9 , 1.99 , 1.999 , 1.9999 ] scores_product_model...dev p=1.9990 1.914574e+03 1.914370e+03 1.914537e+03 1.914388e+03...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
Demo of OPTICS clustering algorithm — sci...
subplot ( G [ 1 , 0 ]) ax3 = plt . subplot ( G [ 1 , 1 ]) ax4 = plt...labels_ == - 1 , 0 ], X [ clust . labels_ == - 1 , 1 ], "k+"...scikit-learn.org/stable/auto_examples/cluster/plot_optics.html -
SGD: convex loss functions — scikit-learn...
>= - 1 ] = ( 1 - z [ z >= - 1 ]) ** 2 loss [ z >= 1.0 ]...([ xmin , 0 , 0 , xmax ], [ 1 , 1 , 0 , 0 ], color = "gold"...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_loss_functions.html -
Visualizing the stock market structure — ...
index ] = 1 dy = y - embedding [ 1 ] dy [ index ] = 1 this_dx =...alphas = np . logspace ( - 1.5 , 1 , num = 10 ) edge_model = covariance...scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html -
8. Dataset loading utilities — scikit-lea...
1. Toy datasets 8.1.1. Iris plants dataset 8.1.2. Diabetes...digits dataset 8.1.4. Linnerrud dataset 8.1.5. Wine recognition dataset...scikit-learn.org/stable/datasets.html -
Demonstrating the different strategies of KBins...
strategies ) + 1 , i ) ax . scatter ( X [:, 0 ], X [:, 1 ], edgecolors.... linspace ( X [:, 1 ] . min (), X [:, 1 ] . max (), 300 ), )...scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_strategies.html -
Displaying estimators and complex pipelines ...
C 1.0 fit_intercept True intercept_scaling 1 class_weight ...C 1.0 fit_intercept True intercept_scaling 1 class_weight ...scikit-learn.org/stable/auto_examples/miscellaneous/plot_estimator_representation.html -
Agglomerative clustering with and without struc...
) t = 1.5 * np . pi * ( 1 + 3 * np . random . rand ( 1 , n_samples..."single" )): plt . subplot ( 1 , 4 , index + 1 ) model = AgglomerativeCluster...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.html -
9. Computing with scikit-learn — scikit-l...
1.1. Scaling with instances using out-of-core...Computing with scikit-learn # 9.1. Strategies to scale computationally:...scikit-learn.org/stable/computing.html