Sequential Skip Prediction

"Sequential skip prediction" is a time series analysis method designed to predict future values in a sequence after skipping certain time points. This method enhances prediction accuracy and robustness by learning long-term dependencies in sequential data. In fields such as finance, meteorology, and healthcare, sequential skip prediction can effectively address issues of missing data and irregular sampling, thereby improving the performance and reliability of decision support systems.