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WenjieDu / SAITS

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516
https://doi.org/10.1016/j.eswa.2023.119619
MIT License
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关于生成数据的一些问题 #38

Closed V50-ikun closed 3 months ago

V50-ikun commented 4 months ago

您好，在代码复现过程中遇到了一些问题，希望您能解答。 1.插补生成的数据与原始数据一样，在ETT测试集中，根据missing_mask可以得知(0,3)这个点应该是手动缺失，但最后生成的值和原始值一摸一样，excel是数据标准化后导出的文件，h5文件是生成的文件。 Snipaste_2024-06-03_14-56-24

2.如果采用自己的数据集，训练过程中的config文件是要自己定义吗？其次config文件夹中的best是自己不断训练出来的吗？

3.最后插补生成的h5文件我想用来进行下游预测工作，可以转为csv导出吗？

WenjieDu commented 4 months ago

Hi there,

Thank you so much for your attention to SAITS! If you find SAITS is helpful to your work, please star⭐️ this repository. Your star is your recognition, which can let others notice SAITS. It matters and is definitely a kind of contribution.

I have received your message and will respond ASAP. Thank you again for your patience! 😃

Best,
Wenjie