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What is Wine Classification with Decision Trees about?

This document loads wine quality data, splits it into training and test sets, scales the features, trains a decision tree classifier on the training set, evaluates it on the test set, and visualizes the trained decision tree. It reports an accuracy of 0.89 and F1 scores of [0.88, 0.85, 0.96] on the three classes. The trained decision tree uses features 9, 6, and 12 to classify instances into the three wine classes.

Author

Nguyen Trung Thinh

Language

EN