About Missing Data (0 values)

[imethanlee]

There is a lot of missing data (those with value 0) in several datasets (such as METR-LA). Did you adopt any interplolation approach (such as linear interplolation) to fill in these missing values?

[MengzhangLI]

There is a lot of missing data (those with value 0) in several datasets (such as METR-LA). Did you adopt any interplolation approach (such as linear interplolation) to fill in these missing values?

Hi, sorry for late reply.

First of all, the result of this model on METR-LA is wrong because the metric of METR-LA, PEMS-BAY, etc is different from PEMS0X. Sorry for my misleading result on first version on ARXIV.

But I can answer this question: right now most model use masked index to solve many zero/null values in METR-LA and PEMS-BAY. When training, the masked index could skip places of those zeor/null to get loss for back propagation.

For example, you can check it from GraphWaveNet:
https://github.com/nnzhan/Graph-WaveNet/blob/6b162e80c59a1d494809252eca055cff93dc66b1/util.py#L177

Best,

[imethanlee]

This helps a lot. Thanks.