COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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pruning
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splitting
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leaf node
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parent node
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Detailed explanation-1: -The most widely used method for splitting a decision tree is the gini index or the entropy. The default method used in sklearn is the gini index for the decision tree classifier.
Detailed explanation-2: -Root Node: It represents the entire population or sample and this further gets divided into two or more homogeneous sets. Splitting: It is a process of dividing a node into two or more sub-nodes. Decision Node: When a sub-node splits into further sub-nodes, then it is called the decision node.
Detailed explanation-3: -The process of splitting a single node into many nodes is known as splitting. A leaf node, also known as a terminal node, is a node that does not break into other nodes. A branch, sometimes known as a sub-tree, is a section of a decision tree. Splitting is not the only concept that is diametrically opposite it.
Detailed explanation-4: -Working of Decision Tree The root node feature is selected based on the results from the Attribute Selection Measure(ASM). The ASM is repeated until a leaf node, or a terminal node cannot be split into sub-nodes.