UNASSIGNED: A Monte Carlo simulation was conducted, varying the levels of non-normality, sample sizes, and levels of communality. The performances of autoencoders and a PCA were compared using the mean square error, mean absolute value, and Euclidian distance. The feasibility of autoencoders with small sample sizes was examined.
UNASSIGNED: With extreme flexibility in decoding representation using linear and non-linear mapping, this study demonstrated that the autoencoder can robustly reduce dimensions, and hence was effective in building the construct validity with a sample size as small as 100. The autoencoders could obtain a smaller mean square error and small Euclidian distance between original dataset and predictions for a small non-normal dataset. Hence, when behavioral scientists attempt to explore the construct validity of a newly designed questionnaire, an autoencoder could also be considered an alternative to a PCA.
未经评估:进行了蒙特卡罗模拟,改变非正态的水平,样本大小,和社区水平。使用均方误差比较了自动编码器和PCA的性能,平均绝对值,和欧几里得距离。研究了小样本自动编码器的可行性。
UNASSIGNED:在使用线性和非线性映射的解码表示中具有极大的灵活性,这项研究表明,自动编码器可以鲁棒地减小尺寸,因此在样本量小至100的情况下有效地构建了结构效度。自编码器可以获得较小的均方误差和原始数据集与小的非正常数据集的预测之间的小的欧几里得距离。因此,当行为科学家试图探索新设计的问卷的结构效度时,自动编码器也可以被认为是PCA的替代方案。