kfoldCVssä
kfoldCVssä is a Finnish term that translates to "in k-fold cross-validation." K-fold cross-validation is a resampling technique used in machine learning to evaluate the performance of a model on unseen data. It is a widely adopted method for assessing how well a predictive model will generalize to an independent dataset.
The process of k-fold cross-validation begins by dividing the entire dataset into a predetermined number, k,
After completing all k iterations, the performance metric of the model is averaged across the k validation