Ensemble methods

Examples concerning the sklearn.ensemble module.

Categorical Feature Support in Gradient Boosting

Categorical Feature Support in Gradient Boosting

Categorical Feature Support in Gradient Boosting
Combine predictors using stacking

Combine predictors using stacking

Combine predictors using stacking
Comparing random forests and the multi-output meta estimator

Comparing random forests and the multi-output meta estimator

Comparing random forests and the multi-output meta estimator
Decision Tree Regression with AdaBoost

Decision Tree Regression with AdaBoost

Decision Tree Regression with AdaBoost
Discrete versus Real AdaBoost

Discrete versus Real AdaBoost

Discrete versus Real AdaBoost
Early stopping of Gradient Boosting

Early stopping of Gradient Boosting

Early stopping of Gradient Boosting
Feature importances with a forest of trees

Feature importances with a forest of trees

Feature importances with a forest of trees
Feature transformations with ensembles of trees

Feature transformations with ensembles of trees

Feature transformations with ensembles of trees
Gradient Boosting Out-of-Bag estimates

Gradient Boosting Out-of-Bag estimates

Gradient Boosting Out-of-Bag estimates
Gradient Boosting regression

Gradient Boosting regression

Gradient Boosting regression
Gradient Boosting regularization

Gradient Boosting regularization

Gradient Boosting regularization
Hashing feature transformation using Totally Random Trees

Hashing feature transformation using Totally Random Trees

Hashing feature transformation using Totally Random Trees
IsolationForest example

IsolationForest example

IsolationForest example
Monotonic Constraints

Monotonic Constraints

Monotonic Constraints
Multi-class AdaBoosted Decision Trees

Multi-class AdaBoosted Decision Trees

Multi-class AdaBoosted Decision Trees
OOB Errors for Random Forests

OOB Errors for Random Forests

OOB Errors for Random Forests
Pixel importances with a parallel forest of trees

Pixel importances with a parallel forest of trees

Pixel importances with a parallel forest of trees
Plot class probabilities calculated by the VotingClassifier

Plot class probabilities calculated by the VotingClassifier

Plot class probabilities calculated by the VotingClassifier
Plot individual and voting regression predictions

Plot individual and voting regression predictions

Plot individual and voting regression predictions
Plot the decision boundaries of a VotingClassifier

Plot the decision boundaries of a VotingClassifier

Plot the decision boundaries of a VotingClassifier
Plot the decision surfaces of ensembles of trees on the iris dataset

Plot the decision surfaces of ensembles of trees on the iris dataset

Plot the decision surfaces of ensembles of trees on the iris dataset
Prediction Intervals for Gradient Boosting Regression

Prediction Intervals for Gradient Boosting Regression

Prediction Intervals for Gradient Boosting Regression
Single estimator versus bagging: bias-variance decomposition

Single estimator versus bagging: bias-variance decomposition

Single estimator versus bagging: bias-variance decomposition
Two-class AdaBoost

Two-class AdaBoost

Two-class AdaBoost