Significance of Cross validation
Cross validation is defined both in Yoga and Science. In Yoga, it substantiates findings from TM research across varied measures and studies. In contrast, Science describes cross validation primarily as a statistical method for evaluating how results from analyses generalize to independent datasets, enhancing predictive model reliability. It involves techniques for comparing validation parameters across multiple methods or laboratories, assessing model performance through data partitioning, and ensuring consistency in results across various studies.
Synonyms: Model validation, Statistical validation
In Dutch: Kruisvalidatie; In Finnish: Ristiin validointi; In Spanish: Validación cruzada
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
The concept of Cross validation in scientific sources
Cross validation involves comparing validation parameters across multiple bioanalytical methods or laboratories for consistency and reliability, as well as evaluating the predictive performance of the Sushrutha Prakriti Inventory using results from diverse data sets.
From: The Malaysian Journal of Medical Sciences
(1) Nested and repeated of this is used for classification models, especially when working with high-dimensional data.[1] (2) A method of validating findings of a study by applying the results to different samples or populations.[2]