Optimal ratio for data splitting
By V. Roshan Joseph. Statistical analysis and data mining, 2022
682 citations recorded by the source corpus.
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. In this article, we show that the optimal training/testing splitting ratio is p:1$$ \sqrt{p}:1 $$ , where p$$ p $$ is the number of parameters in a linear regression model that explains the data well.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/496a270ed280540d62e18fe6ba3f019f9bcfae0e