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05.decision Tree by sylvia.seungyun is a document available to read on EtoBox.

What is 05.decision Tree about?

The document details the application of Decision Tree algorithms to the Iris and Boston housing datasets using Python libraries. It includes steps for loading data, training classifiers and regressors, evaluating model accuracy, and visualizing the decision trees. Key results include high accuracy for the Iris dataset and a moderate R-squared score for the Boston housing dataset.

Author

sylvia.seungyun

Language

EN