2.6 K-fold-based method

K-fold cross validation approach is a resampling procedure used to evaluate machine learning models over a sample data. The bootstrap is another resampling technique that generates multiple datasets by sampling from the original single dataset [13]. A combination of bootstrap sampling, k-fold cross validation, mutual information, and stationary time-series processing with clear sky model is applied in Ref. [13] for solar radiation forecasting. In this method, the cumulative distribution function (CDF) and matching quintile estimation (MQE) are used to determine the prediction interval. Based on the evaluation results, the proposed method demonstrates higher accuracy for forecasting horizons varying between 1 and 6 hours.
