Full cross-validation and generating learning curves for time-series models

Standard cross-validation on time sequence data simply is not doable because of the data model is sequential, which does not lend properly to splitting the data into statistically useful teaching and validation models. However, a model new methodology referred to as Reconstructive Cross-validation would possibly pave the easiest way in direction of performing such a obligatory analysis for predictive models with temporal datasets.