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将最近邻回归共形预测应用于时间序列数据AI 解读

In this paper, we apply conformal prediction to time series data. Conformal prediction isa method that produces predictive regions given a confidence level. The regions outputs arealways valid under the exchangeability assumption. However, this assumption does not holdfor the time series data because there is a link among past, current, and future observations.Consequently, the challenge of applying conformal predictors to the problem of time seriesdata lies in the fact that…

将 k 近邻用于时间序列预测：两种新方法AI 解读

K-nearest neighbors algorithm is one of the prominent techniques used in classification and regression. Despite its simplicity, the k-nearest neighbors has been successfully applied in time series forecasting. However, the selection of the number of neighbors and feature selection is a daunting task. In this paper, we introduce two methodologies to forecasting time series that we refer to as Classical Parameters Tuning in Weighted Nearest Neighbors and Fast Parameters Tuning…