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Define the bagging classifier

In the following exercises you'll work with the Indian Liver Patient dataset from the UCI machine learning repository. Your task is to predict whether a patient suffers from a liver disease using 10 features including Albumin, age and gender. You'll do so using a Bagging Classifier.

This exercise is part of the course

Machine Learning with Tree-Based Models in Python

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Exercise instructions

  • Import DecisionTreeClassifier from sklearn.tree and BaggingClassifier from sklearn.ensemble.

  • Instantiate a DecisionTreeClassifier called dt.

  • Instantiate a BaggingClassifier called bc consisting of 50 trees.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import DecisionTreeClassifier
____

# Import BaggingClassifier
____

# Instantiate dt
dt = ____(random_state=1)

# Instantiate bc
bc = ____(base_estimator=____, n_estimators=____, random_state=1)
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