Computation times¶
02:00.322 total execution time for auto_examples_ensemble files:
Early stopping of Gradient Boosting ( |
00:52.524 |
0.0 MB |
Gradient Boosting regularization ( |
00:21.870 |
0.0 MB |
OOB Errors for Random Forests ( |
00:12.843 |
0.0 MB |
Multi-class AdaBoosted Decision Trees ( |
00:11.056 |
0.0 MB |
Plot the decision surfaces of ensembles of trees on the iris dataset ( |
00:05.109 |
0.0 MB |
Discrete versus Real AdaBoost ( |
00:04.205 |
0.0 MB |
Gradient Boosting Out-of-Bag estimates ( |
00:02.603 |
0.0 MB |
Feature transformations with ensembles of trees ( |
00:02.582 |
0.0 MB |
Two-class AdaBoost ( |
00:01.418 |
0.0 MB |
Gradient Boosting regression ( |
00:01.326 |
0.0 MB |
Single estimator versus bagging: bias-variance decomposition ( |
00:00.830 |
0.0 MB |
Monotonic Constraints ( |
00:00.745 |
0.0 MB |
Plot individual and voting regression predictions ( |
00:00.661 |
0.0 MB |
Comparing random forests and the multi-output meta estimator ( |
00:00.396 |
0.0 MB |
Prediction Intervals for Gradient Boosting Regression ( |
00:00.354 |
0.0 MB |
Feature importances with forests of trees ( |
00:00.350 |
0.0 MB |
IsolationForest example ( |
00:00.303 |
0.0 MB |
Decision Tree Regression with AdaBoost ( |
00:00.298 |
0.0 MB |
Hashing feature transformation using Totally Random Trees ( |
00:00.283 |
0.0 MB |
Plot the decision boundaries of a VotingClassifier ( |
00:00.276 |
0.0 MB |
Plot class probabilities calculated by the VotingClassifier ( |
00:00.245 |
0.0 MB |
Combine predictors using stacking ( |
00:00.030 |
0.0 MB |
Pixel importances with a parallel forest of trees ( |
00:00.013 |
0.0 MB |