APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which is FALSE about Decision Tree
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We can extract RULES from the Decision Tree
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It is good to find relationship of non-linearly correlated data
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it has to formed from a binary tree
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The output can be easily understood by a layman
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Explanation:
Detailed explanation-1: -Explanation: “A decision tree” is constructed with a top-down approach from a “root node” with the partitioning of the “data into subsets” compromising instances with homogenous similar values (homogeneous). A decision tree applies the predictive modeling method followed in statistics, data mining and machine learning.
Detailed explanation-2: -A decision tree is a tree structure (a binary tree or a non-binary tree). Each non-leaf node represents a test on a feature attribute. Each branch represents the output of a feature attribute in a certain value range, and each leaf node stores a category.
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