- Supervised Learning
- Classification
- Regression
- Time Series Forecasting
- Unsupervised Learning
- Clustering
- K-Means Clustering
- Hierarchical Clustering
- Semi-Supervised Learning
- Reinforcement Learning(ML)
- Deep Learning(ML)
- Transfer Learning(ML)
- Ensemble Learning
- Explainable AI (XAI)
- Bayesian Learning
- Decision Trees
- Support Vector Machines (SVMs)
- Instance-Based Learning
- Rule-Based Learning
- Neural Networks
- Evolutionary Algorithms
- Meta-Learning
- Multi-Task Learning
- Metric Learning
- Few-Shot Learning
- Adversarial Learning
- Data Pre Processing
- Natural Language Processing(ML)
Decision Trees QUIZ QUESTIONS
Question: 1
Which of the following is a common method for splitting nodes in a decision tree?
Question: 2
What is the main disadvantage of decision trees in machine learning?
Question: 3
What is the purpose of pruning in decision trees?
Question: 4
Which of the following is a popular algorithm for constructing decision trees?
Question: 5
What is the main difference between classification and regression trees (CART)?
Question: 6
What is the primary purpose of the Random Forest algorithm?
Question: 7
What is the main advantage of using bagging with decision trees?
Question: 8
What is the primary difference between bagging and boosting in the context of decision trees?
Question: 9
What is the primary purpose of the AdaBoost algorithm?
Question: 10
Which of the following is a popular method for splitting nodes in a regression tree?
Question: 11
What is a decision boundary in the context of decision trees?
Question: 12
What is entropy in the context of decision trees?
Question: 13
Which of the following is a common stopping criterion for growing a decision tree?
Question: 14
In the context of decision trees, what is "one-hot encoding" used for?
Question: 15
How do decision trees handle continuous variables?
Question: 16
What is the main disadvantage of using a large maximum depth for a decision tree?
Question: 17
Which of the following techniques can be used to reduce overfitting in decision trees?
Question: 18
What is the primary purpose of the Gradient Boosting Machine (GBM) algorithm?
Question: 19
Which of the following is NOT a common use case for decision trees?
Question: 20
Which of the following is a disadvantage of using decision trees for regression tasks?
Question: 21
In the context of decision trees, what does "feature importance" refer to?
Question: 22
Which of the following is a disadvantage of using decision trees for classification tasks?
Question: 23
Which of the following is an ensemble learning technique that uses decision trees as base learners?
Question: 24
How can decision trees be made more robust to noise in the data?
Question: 25
What is the primary difference between a decision tree and a decision stump?
Question: 26
Which of the following algorithms can be used for both classification and regression tasks?
Question: 27
In a decision tree, what is the purpose of the leaf nodes?
Question: 28
What is a common technique used to reduce the variance of a decision tree?
Question: 29
What is a decision tree in the context of machine learning?
Question: 30
What is the primary advantage of using decision trees in machine learning?