Podcast
Questions and Answers
What is the primary purpose of a Decision Tree?
What is the primary purpose of a Decision Tree?
- Creating outcome branches
- Finding multiple decision rules
- Representing features of a dataset (correct)
- Solving only Regression problems
Which type of problems is a Decision Tree most commonly preferred for solving?
Which type of problems is a Decision Tree most commonly preferred for solving?
- Unsupervised learning problems
- Clustering problems
- Regression problems
- Classification problems (correct)
What do Leaf nodes represent in a Decision Tree?
What do Leaf nodes represent in a Decision Tree?
- Features of a dataset
- Output of decisions (correct)
- Decision rules
- Branches
What does the Root node of a Decision Tree represent?
What does the Root node of a Decision Tree represent?
Which algorithm is commonly used to build a Decision Tree?
Which algorithm is commonly used to build a Decision Tree?
How does a Decision Tree split its branches?
How does a Decision Tree split its branches?
What type of methods are used as a preprocessing step in feature selection?
What type of methods are used as a preprocessing step in feature selection?
Which statistical test is typically used in filter methods to select features based on their correlation with the outcome variable?
Which statistical test is typically used in filter methods to select features based on their correlation with the outcome variable?
What does Pearson’s correlation measure between two continuous variables?
What does Pearson’s correlation measure between two continuous variables?
Which method is used to find a linear combination of features that characterizes or separates classes in a categorical variable?
Which method is used to find a linear combination of features that characterizes or separates classes in a categorical variable?
What does ANOVA stand for and how does it differ from LDA?
What does ANOVA stand for and how does it differ from LDA?
Which method involves finding a linear combination of features by penalizing the absolute size of the regression coefficients?
Which method involves finding a linear combination of features by penalizing the absolute size of the regression coefficients?
What is the main concept behind the Random Forest algorithm?
What is the main concept behind the Random Forest algorithm?
In Random Forest, how are final predictions made?
In Random Forest, how are final predictions made?
What does the greater number of trees in a Random Forest lead to?
What does the greater number of trees in a Random Forest lead to?
What is the purpose of ensemble learning in machine learning?
What is the purpose of ensemble learning in machine learning?
Which technique is Random Forest primarily based on?
Which technique is Random Forest primarily based on?
What problem does having a large number of trees in a Random Forest help to prevent?
What problem does having a large number of trees in a Random Forest help to prevent?
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