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Building and Evaluating Decision Trees by tsar_philip2010 is a document available to read on EtoBox.

What is Building and Evaluating Decision Trees about?

There are several ways to build decision trees from statistical data to classify or predict outcomes. The quality of a tree depends on its accuracy and complexity. Accuracy is measured by parameters like the error rate or variance from predictions. Complexity is measured by the number of leaves, nodes, or longest path in the tree. An optimal tree balances accuracy and complexity, as simpler trees generalize better while more complex trees may overfit the training data. Common techniques include minimizing a

Author

tsar_philip2010

Language

EN