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Ash Ketchump
Ash Ketchump
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Irregular Neural networks - irregular time shifts of output compared to inputs in given time series data sets

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Ash Ketchump
Ash Ketchump
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I have some time series data with multiple features. The output is shifted (I mean the times at which the I have the output values are shifted from the corresponding inputs and also irregularly). I have some idea of what the shifts can be but not exact. Is there a way to use Long Short-Term Memory (LSTM) neural networks which can take into account these irregular shifts? Or any pre-processing that can help before training a LSTM model.?

I have some time series data with multiple features. The output is shifted (I mean the times at which the I have the output values are shifted from the corresponding inputs and irregularly). I have some idea of what the shifts can be but not exact. Is there a way to use Long Short-Term Memory (LSTM) neural networks which can take into account these irregular shifts? Or any pre-processing that can help before training a LSTM model.

I have some time series data with multiple features. The output is shifted (I mean the times at which I have the output values are shifted from the corresponding inputs and also irregularly). I have some idea of what the shifts can be but not exact. Is there a way to use Long Short-Term Memory (LSTM) neural networks which can take into account these irregular shifts? Or any pre-processing that can help before training a LSTM model?

spelled out long short term memory for those who don't know what LSTM is. Fixed a few other things
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edit approved Jan 22 at 2:12
Rick Hass
edit approved Jan 22 at 2:12
Rick Hass
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irregular Irregular time shifts of output compared to inputs in given time series data sets

I have some time series data with an multiplemultiple features. The output is shifted (I mean the times at which the I have the output values are shifted from the corresponding inputs and irregularly). I have some idea of what the shifts can be but not exact. Is there a way to use LSTMLong Short-Term Memory (LSTM) neural networks which can take into account these irregular shifts? Or any pre-processing that can help before training a LSTM model.

irregular time shifts of output compared to inputs in given time series data sets

I have some time series data with an multiple features. The output is shifted (I mean the times at which the I have the output values are shifted from the corresponding inputs and irregularly). I have some idea of what the shifts can be but not exact. Is there a way to use LSTM neural networks which can take into account these irregular shifts? Or any pre-processing that can help before training a LSTM model.

Irregular time shifts of output compared to inputs in given time series data sets

I have some time series data with multiple features. The output is shifted (I mean the times at which the I have the output values are shifted from the corresponding inputs and irregularly). I have some idea of what the shifts can be but not exact. Is there a way to use Long Short-Term Memory (LSTM) neural networks which can take into account these irregular shifts? Or any pre-processing that can help before training a LSTM model.

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Ash Ketchump
Ash Ketchump
  • 11
  • 2