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What is Kurtosis in Decision Tree Modeling about?

This paper proposes a method for assessing overfitting and underfitting in decision tree models by analyzing the kurtosis of residuals, suggesting that mesokurtic residuals indicate a well-fitted model. The author draws on industry experiences to illustrate how kurtosis can reflect the true information extracted from data, with platykurtic residuals signaling underfitting and leptokurtic residuals indicating overfitting. The conjecture posits that kurtosis serves as a useful metric for model evaluation acro

Author

olafmiler30

Language

EN