Comments (1)
您好,可以看一下代码,是整体来reshape的。这是因为当使用value embedding将原始数据映射至特征空间之后,特征的各个channel是等价的,所以也就没有区分不同的变量。
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Related Issues (20)
- 进行long term forecasting,设置features参数为MS时,target参数无法正确选中目标数据列 HOT 2
- 关于NSTransformer ECL scripts HOT 1
- 论文中其他SOTA方法的数据来源 HOT 1
- TimeSeries classification task HOT 1
- How to obtain PEMS and Solar-Energy datasets in iTransformer HOT 1
- 关于开源代码和论文实验结果复现问题 HOT 3
- Koopa module - torch.linalg.lstsq call
- Koopa module - seg_len parmeter HOT 2
- Something wrong on short_term_forecast HOT 4
- Insufficient GPU memory for the long term forecast task HOT 1
- 想问一下为什么我自己的数据 只有两列,会出现Nan这种情况 HOT 2
- 无法复现结果,用了torch1.7.1也一样不行
- add SCINet into baseline
- Non-overlapping sliding window for anomaly detection experiments HOT 1
- 分类实验结果无法复现 HOT 2
- multivariable test results HOT 1
- Error in Timesnet Short term Forecasting Model Training (modelConfig)
- CPU-heavy operation slowing training HOT 3
- Would you mind add "One Fits All: Power General Time Series Analysis by Pretrained LM“ HOT 1
- May I ask if the anomaly detection methods implemented in tslib need to be classified? Are they based on forecasting or reconstruction? HOT 1
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