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Questions and Answers
What is the process of dividing a node into two or more sub-nodes called?
What is the process of dividing a node into two or more sub-nodes called?
What is the topmost node in a decision tree structure that represents the entire population or sample?
What is the topmost node in a decision tree structure that represents the entire population or sample?
What is a node that does not split further called?
What is a node that does not split further called?
What is the process of removing sub-nodes of a decision node called?
What is the process of removing sub-nodes of a decision node called?
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What is a subsection of the entire tree called?
What is a subsection of the entire tree called?
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What is the node that splits into further sub-nodes called?
What is the node that splits into further sub-nodes called?
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What is the primary criterion for selecting the best attribute to split the data in a decision tree?
What is the primary criterion for selecting the best attribute to split the data in a decision tree?
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What is the purpose of recursively partitioning the data in a decision tree?
What is the purpose of recursively partitioning the data in a decision tree?
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What is a common stopping criterion for building a decision tree?
What is a common stopping criterion for building a decision tree?
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What is a characteristic of a decision tree that makes it accessible to non-experts?
What is a characteristic of a decision tree that makes it accessible to non-experts?
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What is a disadvantage of a single decision tree?
What is a disadvantage of a single decision tree?
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What is the primary advantage of using a random forest over a single decision tree?
What is the primary advantage of using a random forest over a single decision tree?
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What is the primary mechanism by which the random forest algorithm generates a prediction?
What is the primary mechanism by which the random forest algorithm generates a prediction?
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What is the role of the decision tree algorithm in the random forest analogy?
What is the role of the decision tree algorithm in the random forest analogy?
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What is the outcome of the voting procedure in the random forest algorithm?
What is the outcome of the voting procedure in the random forest algorithm?
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How does the random forest algorithm handle the feature importance?
How does the random forest algorithm handle the feature importance?
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What is the application of the random forest algorithm in the context of loan applications?
What is the application of the random forest algorithm in the context of loan applications?
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What is the relationship between the random forest algorithm and the Boruta algorithm?
What is the relationship between the random forest algorithm and the Boruta algorithm?
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