Linear regression

Algorithm

Statistics

Data mining

Computer science

Mathematics

Statistical hypothesis testing

Artificial intelligence

Training set

Machine learning

Statistical Analysis and Data Mining The ASA Data Science Journal

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 splitting ratio is $\sqrt{p}:1$, where $p$ is the number of parameters in a linear regression model that explains the data well.

Optimal ratio for data splitting