Comments (7)
The second dimension T
is timesteps
, which means seq_len
, whose value is 12
The last dimension D
is the speed
corresponding to a certain time
~
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Hi zhengxu, the input data is (N x T x V x D), where N is the number of training examples, T corresponds to the number of input steps, V denotes the number of nodes, and D represents the input feature dimension, here 2 consists of 1) the speed and 2) the time.
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About the second dim, what 'the time' means to be specific?
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Hi, liyaguang @liyaguang thanks for sharing the great work. actually I don't think the second input feature dimensions is time. because I find the value is something like float in In scientific counting, the value is between [0,1] , mean value 0.497, max value 0.997, min value 0; so can you provide some evidence for the second feature dimenson please?
thanks and best regards,
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Hi @yansicing , thanks for your explaination, but I still have questions here. You said "D is the speed
corresponding to a certain time
", and I'm wondering which time
it is. I was thinking the authors were using 5-minutes average speed, right? If so, what is the time
that the speed
corresponds to? Thank you very much!
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Hi @chenz97, @mengmeng716, the time dimension refers to the normalized time in a day, e.g., 0:00 am will be 0, while 12pm will be 0.5.
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Hi @liyaguang , I got it. Thanks a lot.
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Related Issues (20)
- About the graph of the paper
- About the graph of the paper
- Why are some speed data negative?
- scaler transform in load_dataset function Causing speed data negative
- sensors correlations or node interactions and how to interpret the model's output
- Input 'b' of 'SparseTensorDenseMatMul' Op has type float32 that does not match type float64 of argument 'a_values'. HOT 2
- Wrong sensor IDs for MetrLA? HOT 8
- Predictions near mean value
- 关于数据的输入问题
- train.py
- Sensor id and data series
- Result Charts - One Example Sensor or Mean of the entire dataset
- Tensorflow 2 for DCRNN models HOT 2
- reproduce results HOT 13
- nothing HOT 1
- A question about the code HOT 1
- Diffusion convolution is not found in code
- A question about changing predicting time interval
- How to train model use different dataset
- isolated nodes
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