Choosing the right ensemble to tame an overfitting high-variance tree.
Codepython
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
# Goal: our single deep decision tree OVERFITS (high variance, low bias).
# We want an ensemble that primarily REDUCES VARIANCE.
model = AdaBoostClassifier(n_estimators=100)
model.fit(X_train, y_train)
The goal is to reduce the variance of an overfitting tree. What is the bug?