Question

Briefly outline the major steps of decision tree classification

Answer 1

Decision tree builds classification or regression models in the form of a tree structure. It breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The final result is a tree with decision nodes and leaf nodes. A decision node (e.g., Outlook) has two or more branches (e.g., Sunny, Overcast and Rainy). Leaf node (e.g., Play) represents a classification or decision. The topmost decision node in a tree which corresponds to the best predictor called root node. Decision trees can handle both categorical and numerical data.

Answer 2

The major steps of decision tree classification:

• Decision tree builds allocation or regression models in the shape of a tree structure.
• It inculcates a dataset into lesser and lesser subsets while at the same time an associated decision tree is incrementally advanced.
• Leaf node (e.g., Play) depicted a classification or decision.
• The topmost decision node in a tree which corresponds to the best predictor known as root node.
• Decision trees can able to handle both "categorical and numerical data".

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Decision tree advantages and disadvantages

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