Frequently asked Questions What is cross-validation in machine learning? Cross-validation is a statistical method used to evaluate machine learning models.

Data validation in machine learning plays a critical role in ensuring that data sets adhere to specific project criteria and affirming the effectiveness of prior cleaning and transformation efforts.

We present evidence that prioritizing minimal out-of-sample error, identified through cross-validation and stochastic ensemble methods, in PMT tool development can substantially improve the ...

Identification of the optimal machine learning pipelines and external validation results. The performance of best performing pipelines in the external validation cohort of 726 patients in comparison ...