Computation times

01:05.502 total execution time for auto_examples_linear_model files:

Comparing various online solvers (plot_sgd_comparison.py)

00:38.787

0.0 MB

Lasso on dense and sparse data (plot_lasso_dense_vs_sparse_data.py)

00:06.419

0.0 MB

Robust linear estimator fitting (plot_robust_fit.py)

00:04.830

0.0 MB

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

00:02.418

0.0 MB

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

00:01.538

0.0 MB

Theil-Sen Regression (plot_theilsen.py)

00:01.488

0.0 MB

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

00:01.010

0.0 MB

Bayesian Ridge Regression (plot_bayesian_ridge.py)

00:00.996

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

00:00.699

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Lasso and Elastic Net (plot_lasso_coordinate_descent_path.py)

00:00.667

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

00:00.621

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

00:00.558

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SGD: Penalties (plot_sgd_penalties.py)

00:00.512

0.0 MB

Curve Fitting with Bayesian Ridge Regression (plot_bayesian_ridge_curvefit.py)

00:00.494

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

00:00.487

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Orthogonal Matching Pursuit (plot_omp.py)

00:00.478

0.0 MB

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

00:00.451

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

00:00.350

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

00:00.288

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

00:00.256

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SGD: convex loss functions (plot_sgd_loss_functions.py)

00:00.242

0.0 MB

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

00:00.228

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Robust linear model estimation using RANSAC (plot_ransac.py)

00:00.222

0.0 MB

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

00:00.218

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Lasso path using LARS (plot_lasso_lars.py)

00:00.195

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Logistic function (plot_logistic.py)

00:00.192

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Polynomial interpolation (plot_polynomial_interpolation.py)

00:00.192

0.0 MB

SGD: Maximum margin separating hyperplane (plot_sgd_separating_hyperplane.py)

00:00.179

0.0 MB

SGD: Weighted samples (plot_sgd_weighted_samples.py)

00:00.169

0.0 MB

Logistic Regression 3-class Classifier (plot_iris_logistic.py)

00:00.162

0.0 MB

Linear Regression Example (plot_ols.py)

00:00.102

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Tweedie regression on insurance claims (plot_tweedie_regression_insurance_claims.py)

00:00.014

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Early stopping of Stochastic Gradient Descent (plot_sgd_early_stopping.py)

00:00.011

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

00:00.010

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

00:00.010

0.0 MB

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

00:00.008

0.0 MB