Problem 2: (Decision Tree classifier on Iris dataset) oad the Iris dataset from sklearn. Split the dataset into training and testing parts. Use decision tree lassifier. Use “entropy" as the classification criteria. Try maximum tree depths of 2, 3, and 4. Plot the rees for each case. Compare the classification performance.

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Problem 2: (Decision Tree classifier on Iris dataset)
Load the Iris dataset from sklearn. Split the dataset into training and testing parts. Use decision tree
classifier. Use "entropy" as the classification criteria. Try maximum tree depths of 2, 3, and 4. Plot the
trees for each case. Compare the classification performance.
Transcribed Image Text:Problem 2: (Decision Tree classifier on Iris dataset) Load the Iris dataset from sklearn. Split the dataset into training and testing parts. Use decision tree classifier. Use "entropy" as the classification criteria. Try maximum tree depths of 2, 3, and 4. Plot the trees for each case. Compare the classification performance.
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