Optimal ratio for data splitting

Abstract It is common to split a dataset into training and testing sets before fitting a statistical or machine learning model. However, there is no clear guidance on how much data should be used for training and testing.

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• 1 However, there is no clear guidance on how much data should be used for training and testing.
• 2 In this article, we show that the optimal training/testing splitting ratio is , where is the number of parameters in a linear regression model that explains the data well.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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