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Understanding Decision Tree Induction by Aryasree M.D is a document available to read on EtoBox.

A decision tree is a structure used in data mining to classify instances by sorting them from the root node to a leaf node. Each internal node represents a test on an attribute, each branch represents an outcome of the test, and each leaf node provides a classification label. Decision trees are easy to understand and interpret, can handle both numerical and categorical data, and require little data preparation. The ID3 and C4.5 algorithms use a greedy approach to recursively build decision trees from a trai

Author

Aryasree M.D

Language

EN