Computation times¶
03:03.509 total execution time for auto_examples_ensemble files:
Early stopping of Gradient Boosting ( |
01:05.832 |
0.0 MB |
Gradient Boosting regularization ( |
00:29.186 |
0.0 MB |
OOB Errors for Random Forests ( |
00:28.011 |
0.0 MB |
Multi-class AdaBoosted Decision Trees ( |
00:16.194 |
0.0 MB |
Plot the decision surfaces of ensembles of trees on the iris dataset ( |
00:10.607 |
0.0 MB |
Discrete versus Real AdaBoost ( |
00:07.668 |
0.0 MB |
Gradient Boosting Out-of-Bag estimates ( |
00:06.384 |
0.0 MB |
Feature transformations with ensembles of trees ( |
00:03.816 |
0.0 MB |
Two-class AdaBoost ( |
00:02.933 |
0.0 MB |
Gradient Boosting regression ( |
00:02.351 |
0.0 MB |
Single estimator versus bagging: bias-variance decomposition ( |
00:01.985 |
0.0 MB |
Monotonic Constraints ( |
00:01.455 |
0.0 MB |
Plot individual and voting regression predictions ( |
00:01.117 |
0.0 MB |
Prediction Intervals for Gradient Boosting Regression ( |
00:00.985 |
0.0 MB |
Comparing random forests and the multi-output meta estimator ( |
00:00.864 |
0.0 MB |
Plot the decision boundaries of a VotingClassifier ( |
00:00.761 |
0.0 MB |
IsolationForest example ( |
00:00.753 |
0.0 MB |
Decision Tree Regression with AdaBoost ( |
00:00.724 |
0.0 MB |
Feature importances with forests of trees ( |
00:00.702 |
0.0 MB |
Hashing feature transformation using Totally Random Trees ( |
00:00.589 |
0.0 MB |
Plot class probabilities calculated by the VotingClassifier ( |
00:00.576 |
0.0 MB |
Combine predictors using stacking ( |
00:00.012 |
0.0 MB |
Pixel importances with a parallel forest of trees ( |
00:00.005 |
0.0 MB |