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In Decision Trees, what does the Gini impurity measure?

Practice Questions

Q1
In Decision Trees, what does the Gini impurity measure?
  1. The accuracy of the model
  2. The purity of a node
  3. The depth of the tree
  4. The number of features used

Questions & Step-by-Step Solutions

In Decision Trees, what does the Gini impurity measure?
  • Step 1: Understand that a Decision Tree is a way to make decisions based on data.
  • Step 2: Know that each point in the tree is called a 'node'.
  • Step 3: Realize that nodes can have different categories or classes (like 'yes' or 'no').
  • Step 4: Gini impurity is a number that tells us how mixed the classes are at a node.
  • Step 5: A Gini impurity of 0 means all items in the node belong to one class (pure).
  • Step 6: A higher Gini impurity means the classes are mixed (impure).
  • Step 7: We use Gini impurity to find the best way to split the data at each node to make it more pure.
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