CAP

该数据集包含了与多种生理状态相关的脑电图数据点，特别关注非快速眼动（NREM）睡眠周期以及与睡眠障碍相关的模式。此外，该数据集还包括了针对机器学习模型的超参数调整，其中包含了优化分类准确性的特定步长（p）和窗口大小（w）值。该数据集的任务是识别和分类脑电图数据中的周期性交替模式。

This dataset contains electroencephalogram (EEG) data points associated with various physiological states, with a particular focus on non-rapid eye movement (NREM) sleep cycles and patterns related to sleep disorders. In addition, the dataset also includes hyperparameter tuning for machine learning models, encompassing specific step size (p) and window size (w) values that optimize classification accuracy. The task of this dataset is to identify and classify periodic alternating patterns within electroencephalogram data.