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The document describes implementing the ID3 decision tree algorithm. It includes definitions of key terms like entropy and information gain used in ID3. The procedure of ID3 is explained which starts with the root node and recursively builds the tree by splitting on the attribute with highest information gain at each node. A tennis dataset is used and the Python code provided implements the ID3 algorithm to build a decision tree to classify new samples.

Author
shivanshkatiyar.sk
Language
EN

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