Computation times

00:27.790 total execution time for auto_examples_linear_model files:

Comparing various online solvers (plot_sgd_comparison.py)

00:15.495

0.0 MB

Robust linear estimator fitting (plot_robust_fit.py)

00:02.421

0.0 MB

Lasso on dense and sparse data (plot_lasso_dense_vs_sparse_data.py)

00:02.186

0.0 MB

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

00:01.190

0.0 MB

Theil-Sen Regression (plot_theilsen.py)

00:00.779

0.0 MB

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

00:00.680

0.0 MB

Bayesian Ridge Regression (plot_bayesian_ridge.py)

00:00.508

0.0 MB

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

00:00.506

0.0 MB

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

00:00.384

0.0 MB

Lasso and Elastic Net (plot_lasso_coordinate_descent_path.py)

00:00.339

0.0 MB

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

00:00.301

0.0 MB

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

00:00.262

0.0 MB

SGD: Penalties (plot_sgd_penalties.py)

00:00.260

0.0 MB

Curve Fitting with Bayesian Ridge Regression (plot_bayesian_ridge_curvefit.py)

00:00.243

0.0 MB

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

00:00.234

0.0 MB

Orthogonal Matching Pursuit (plot_omp.py)

00:00.232

0.0 MB

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

00:00.221

0.0 MB

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

00:00.182

0.0 MB

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

00:00.145

0.0 MB

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

00:00.128

0.0 MB

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

00:00.119

0.0 MB

Robust linear model estimation using RANSAC (plot_ransac.py)

00:00.112

0.0 MB

SGD: convex loss functions (plot_sgd_loss_functions.py)

00:00.111

0.0 MB

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

00:00.107

0.0 MB

Logistic function (plot_logistic.py)

00:00.102

0.0 MB

Polynomial interpolation (plot_polynomial_interpolation.py)

00:00.100

0.0 MB

Lasso path using LARS (plot_lasso_lars.py)

00:00.096

0.0 MB

Logistic Regression 3-class Classifier (plot_iris_logistic.py)

00:00.090

0.0 MB

SGD: Weighted samples (plot_sgd_weighted_samples.py)

00:00.087

0.0 MB

SGD: Maximum margin separating hyperplane (plot_sgd_separating_hyperplane.py)

00:00.086

0.0 MB

Linear Regression Example (plot_ols.py)

00:00.052

0.0 MB

Tweedie regression on insurance claims (plot_tweedie_regression_insurance_claims.py)

00:00.009

0.0 MB

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

00:00.007

0.0 MB

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

00:00.007

0.0 MB

Early stopping of Stochastic Gradient Descent (plot_sgd_early_stopping.py)

00:00.006

0.0 MB

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

00:00.004

0.0 MB