10 Questions
Which of the following is NOT a characteristic of Decision Trees?
They are black box models
What is the purpose of the root node in a Decision Tree?
To split the data based on the most important feature
What is the purpose of the leaf nodes in a Decision Tree?
To represent the final prediction
What is the role of entropy or Gini impurity in Decision Tree construction?
To measure the impurity or uncertainty of a node
Which of the following is a hyperparameter in Decision Tree models?
The maximum depth of the tree
What is the purpose of visualizing a Decision Tree?
To interpret the decision-making process
What is the role of decision boundaries in a Decision Tree?
To separate the data into distinct regions for different classes
Which of the following is a common issue that can occur in Decision Trees?
Overfitting
What is the advantage of using Decision Trees over black box models?
Interpretability and transparency of the decision-making process
Which of the following is a disadvantage of Decision Trees?
Instability to small changes in the data
Test your knowledge on hyperparameter tuning in decision trees, focusing on Gini impurity versus Entropy and the impact of setting the max_depth parameter. Learn about the decision boundaries and node splits in a decision tree.
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