Computation times¶
04:10.414 total execution time for auto_examples_linear_model files:
Early stopping of Stochastic Gradient Descent ( |
01:18.237 |
0.0 MB |
Poisson regression and non-normal loss ( |
01:03.386 |
0.0 MB |
MNIST classification using multinomial logistic + L1 ( |
00:29.403 |
0.0 MB |
Tweedie regression on insurance claims ( |
00:28.892 |
0.0 MB |
Comparing various online solvers ( |
00:22.053 |
0.0 MB |
Multiclass sparse logistic regression on 20newgroups ( |
00:15.094 |
0.0 MB |
Robust linear estimator fitting ( |
00:02.588 |
0.0 MB |
Lasso on dense and sparse data ( |
00:01.512 |
0.0 MB |
Lasso model selection: Cross-Validation / AIC / BIC ( |
00:01.425 |
0.0 MB |
Theil-Sen Regression ( |
00:00.760 |
0.0 MB |
L1 Penalty and Sparsity in Logistic Regression ( |
00:00.696 |
0.0 MB |
Automatic Relevance Determination Regression (ARD) ( |
00:00.651 |
0.0 MB |
Bayesian Ridge Regression ( |
00:00.611 |
0.0 MB |
Lasso and Elastic Net ( |
00:00.447 |
0.0 MB |
Plot Ridge coefficients as a function of the L2 regularization ( |
00:00.420 |
0.0 MB |
Curve Fitting with Bayesian Ridge Regression ( |
00:00.352 |
0.0 MB |
Plot multinomial and One-vs-Rest Logistic Regression ( |
00:00.347 |
0.0 MB |
Joint feature selection with multi-task Lasso ( |
00:00.338 |
0.0 MB |
Sparsity Example: Fitting only features 1 and 2 ( |
00:00.308 |
0.0 MB |
Orthogonal Matching Pursuit ( |
00:00.306 |
0.0 MB |
SGD: Penalties ( |
00:00.301 |
0.0 MB |
Ordinary Least Squares and Ridge Regression Variance ( |
00:00.282 |
0.0 MB |
Plot Ridge coefficients as a function of the regularization ( |
00:00.198 |
0.0 MB |
Regularization path of L1- Logistic Regression ( |
00:00.185 |
0.0 MB |
Plot multi-class SGD on the iris dataset ( |
00:00.179 |
0.0 MB |
SGD: convex loss functions ( |
00:00.175 |
0.0 MB |
HuberRegressor vs Ridge on dataset with strong outliers ( |
00:00.163 |
0.0 MB |
Lasso and Elastic Net for Sparse Signals ( |
00:00.152 |
0.0 MB |
Robust linear model estimation using RANSAC ( |
00:00.152 |
0.0 MB |
Polynomial interpolation ( |
00:00.127 |
0.0 MB |
Logistic function ( |
00:00.119 |
0.0 MB |
Lasso path using LARS ( |
00:00.116 |
0.0 MB |
SGD: Weighted samples ( |
00:00.107 |
0.0 MB |
SGD: Maximum margin separating hyperplane ( |
00:00.101 |
0.0 MB |
Logistic Regression 3-class Classifier ( |
00:00.099 |
0.0 MB |
Non-negative least squares ( |
00:00.083 |
0.0 MB |
Linear Regression Example ( |
00:00.049 |
0.0 MB |