Age and Gender

该数据集是一套本地数据集，用于对个人的年龄和性别进行分类，其基础数据来源于原始的静息态脑电图。在性别分类上，该数据集已达到94.53%的准确率；在年龄分类上，准确率亦高达87.79%。所涉及的任务是对年龄和性别的分类研究。

This is a local dataset developed for age and gender classification of individual subjects. Its foundational data is sourced from raw resting-state electroencephalogram (EEG) recordings. For gender classification, this dataset achieves an accuracy of 94.53%, while its accuracy for age classification reaches as high as 87.79%. The tasks involved focus on age and gender classification research.