Computation times

00:26.412 total execution time for auto_examples_linear_model files:

Comparing various online solvers (plot_sgd_comparison.py)

00:15.764

0.0 MB

Robust linear estimator fitting (plot_robust_fit.py)

00:02.069

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Lasso on dense and sparse data (plot_lasso_dense_vs_sparse_data.py)

00:02.069

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Lasso model selection: Cross-Validation / AIC / BIC (plot_lasso_model_selection.py)

00:00.934

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Theil-Sen Regression (plot_theilsen.py)

00:00.640

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L1 Penalty and Sparsity in Logistic Regression (plot_logistic_l1_l2_sparsity.py)

00:00.595

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Bayesian Ridge Regression (plot_bayesian_ridge.py)

00:00.437

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Automatic Relevance Determination Regression (ARD) (plot_ard.py)

00:00.434

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Plot Ridge coefficients as a function of the L2 regularization (plot_ridge_coeffs.py)

00:00.315

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Lasso and Elastic Net (plot_lasso_coordinate_descent_path.py)

00:00.294

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Plot multinomial and One-vs-Rest Logistic Regression (plot_logistic_multinomial.py)

00:00.253

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Joint feature selection with multi-task Lasso (plot_multi_task_lasso_support.py)

00:00.239

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SGD: Penalties (plot_sgd_penalties.py)

00:00.223

0.0 MB

Curve Fitting with Bayesian Ridge Regression (plot_bayesian_ridge_curvefit.py)

00:00.220

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Orthogonal Matching Pursuit (plot_omp.py)

00:00.195

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Ordinary Least Squares and Ridge Regression Variance (plot_ols_ridge_variance.py)

00:00.195

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Sparsity Example: Fitting only features 1 and 2 (plot_ols_3d.py)

00:00.185

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Plot Ridge coefficients as a function of the regularization (plot_ridge_path.py)

00:00.144

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Plot multi-class SGD on the iris dataset (plot_sgd_iris.py)

00:00.124

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Regularization path of L1- Logistic Regression (plot_logistic_path.py)

00:00.120

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SGD: convex loss functions (plot_sgd_loss_functions.py)

00:00.108

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HuberRegressor vs Ridge on dataset with strong outliers (plot_huber_vs_ridge.py)

00:00.104

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Lasso and Elastic Net for Sparse Signals (plot_lasso_and_elasticnet.py)

00:00.099

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Robust linear model estimation using RANSAC (plot_ransac.py)

00:00.099

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Polynomial interpolation (plot_polynomial_interpolation.py)

00:00.089

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Lasso path using LARS (plot_lasso_lars.py)

00:00.087

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Logistic function (plot_logistic.py)

00:00.082

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SGD: Maximum margin separating hyperplane (plot_sgd_separating_hyperplane.py)

00:00.075

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Logistic Regression 3-class Classifier (plot_iris_logistic.py)

00:00.071

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SGD: Weighted samples (plot_sgd_weighted_samples.py)

00:00.070

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Linear Regression Example (plot_ols.py)

00:00.050

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Tweedie regression on insurance claims (plot_tweedie_regression_insurance_claims.py)

00:00.008

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Early stopping of Stochastic Gradient Descent (plot_sgd_early_stopping.py)

00:00.006

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Multiclass sparse logistic regression on 20newgroups (plot_sparse_logistic_regression_20newsgroups.py)

00:00.005

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MNIST classification using multinomial logistic + L1 (plot_sparse_logistic_regression_mnist.py)

00:00.005

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Poisson regression and non-normal loss (plot_poisson_regression_non_normal_loss.py)

00:00.004

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