Computation timesΒΆ
12:25.555 total execution time for auto_examples_linear_model files:
Comparing various online solvers (plot_sgd_comparison.py) |
08:46.403 | 0.0 MB |
Regularization path of L1- Logistic Regression (plot_logistic_path.py) |
00:51.874 | 0.0 MB |
Lasso on dense and sparse data (plot_lasso_dense_vs_sparse_data.py) |
00:50.225 | 0.0 MB |
Robust linear estimator fitting (plot_robust_fit.py) |
00:39.148 | 0.0 MB |
Theil-Sen Regression (plot_theilsen.py) |
00:12.856 | 0.0 MB |
Lasso model selection: Cross-Validation / AIC / BIC (plot_lasso_model_selection.py) |
00:08.777 | 0.0 MB |
Automatic Relevance Determination Regression (ARD) (plot_ard.py) |
00:07.360 | 0.0 MB |
L1 Penalty and Sparsity in Logistic Regression (plot_logistic_l1_l2_sparsity.py) |
00:05.781 | 0.0 MB |
Bayesian Ridge Regression (plot_bayesian_ridge.py) |
00:04.939 | 0.0 MB |
Orthogonal Matching Pursuit (plot_omp.py) |
00:03.881 | 0.0 MB |
Lasso and Elastic Net (plot_lasso_coordinate_descent_path.py) |
00:03.695 | 0.0 MB |
Plot Ridge coefficients as a function of the L2 regularization (plot_ridge_coeffs.py) |
00:03.643 | 0.0 MB |
Plot multinomial and One-vs-Rest Logistic Regression (plot_logistic_multinomial.py) |
00:03.479 | 0.0 MB |
SGD: Penalties (plot_sgd_penalties.py) |
00:03.221 | 0.0 MB |
Joint feature selection with multi-task Lasso (plot_multi_task_lasso_support.py) |
00:02.758 | 0.0 MB |
Sparsity Example: Fitting only features 1 and 2 (plot_ols_3d.py) |
00:02.249 | 0.0 MB |
Ordinary Least Squares and Ridge Regression Variance (plot_ols_ridge_variance.py) |
00:02.052 | 0.0 MB |
Plot Ridge coefficients as a function of the regularization (plot_ridge_path.py) |
00:01.829 | 0.0 MB |
Plot multi-class SGD on the iris dataset (plot_sgd_iris.py) |
00:01.308 | 0.0 MB |
HuberRegressor vs Ridge on dataset with strong outliers (plot_huber_vs_ridge.py) |
00:01.083 | 0.0 MB |
SGD: convex loss functions (plot_sgd_loss_functions.py) |
00:01.082 | 0.0 MB |
Lasso and Elastic Net for Sparse Signals (plot_lasso_and_elasticnet.py) |
00:00.925 | 0.0 MB |
Robust linear model estimation using RANSAC (plot_ransac.py) |
00:00.917 | 0.0 MB |
Lasso path using LARS (plot_lasso_lars.py) |
00:00.916 | 0.0 MB |
SGD: Weighted samples (plot_sgd_weighted_samples.py) |
00:00.899 | 0.0 MB |
Logistic Regression 3-class Classifier (plot_iris_logistic.py) |
00:00.849 | 0.0 MB |
Polynomial interpolation (plot_polynomial_interpolation.py) |
00:00.848 | 0.0 MB |
Logistic function (plot_logistic.py) |
00:00.811 | 0.0 MB |
SGD: Maximum margin separating hyperplane (plot_sgd_separating_hyperplane.py) |
00:00.789 | 0.0 MB |
Linear Regression Example (plot_ols.py) |
00:00.484 | 0.0 MB |
MNIST classfification using multinomial logistic + L1 (plot_sparse_logistic_regression_mnist.py) |
00:00.394 | 0.0 MB |
Early stopping of Stochastic Gradient Descent (plot_sgd_early_stopping.py) |
00:00.050 | 0.0 MB |
Multiclass sparse logisitic regression on newgroups20 (plot_sparse_logistic_regression_20newsgroups.py) |
00:00.028 | 0.0 MB |