This dataset provides a collection of synthetic time series designed for benchmarking forecasting models in controlled, unbiased conditions. The data are generated from combinations of sinusoidal sign
The dataset used in this paper is a collection of synthetic oscillating time series, including monochromatic, amplitude- and frequency-modulated sine waves.
Global feature importance methods are one of the core tools for interpreting the role of explanatory variables in machine learning models, however, using them more complex forecasting tasks in