Decision Tree

Important Interview Questions On Decision Tree Machine Learning Algorithm

Decision Tree Machine Learning Algorithms is a very important Machine Learning Algorithm through which we can solve both classification and regression problem statements. Decision Tree is also a base tree that is used in Bagging and Bossting techniques such as Random Forest and Xgboost Classification And Regression Algorithms.

All the important questions that can be asked in a Decision Tree are given below

Decision Tree Classifier And Regressor

Interview Questions:

  1. Decision Tree
  2. Entropy, Information Gain, Gini Impurity
  3. Decision Tree Working For Categorical and Numerical Features
  4. What are the scenarios where Decision Tree works well
  5. Decision Tree Low Bias And High Variance- Overfitting
  6. Hyperparameter Techniques
  7. Library used for constructing decision tree
  8. Impact of Outliers Of Decision Tree
  9. Impact of mising values on Decision Tree
  10. Does Decision Tree require Feature Scaling

First thing is to understand how decision tree works and how we split the decision tree based on entropy, Information gain and Gini impurity. You can check the below videos for the same

Entropy In Decision Tree

Information Gain Intuition

Gini Impurity

And Finally you need to understand how to visualize Decision Tree

Practical Implementation


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