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Machine Learning

Tree Based Methods in Machine Learning

Interview questions on Tree Based Methods in Machine Learning.

20 questions

All subtopicsDecision TreesEnsemble LearningRandom ForestBoosting based Algorithms

Decision Trees

Q2. What is the purpose of decision trees in machine learning?

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Decision Trees

Q4. What is over-fitting in decision trees, and how can it be prevented?

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Decision Trees

Q5. What are some common impurity measures used in decision tree algorithms?

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Decision Trees

Q6. List down pros and cons of different splitting criteria?

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Decision Trees

Q8. Can decision trees handle categorical data, and how is it done?

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Decision Trees

Q9. What are some advantages of decision trees in machine learning?

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Decision Trees

Q13. What are the steps involved in building a decision tree with ID3?

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Decision Trees

Q17. Can you explain how the concept of entropy is used in ID3?

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Decision Trees

Q18. What are different criteria along which the implementation of DTs varies?

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Decision Trees

Q19. What is the difference between CART and ID3/C4.5?

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