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Multidimensional time series RNN using Tensorflow. Is this possible with an LSTM cell or similar?

I am looking for examples of building a multidimensional RNN time series using Tensorflow. Is this possible with an LSTM cell or similar?

eg. The data may look something like this:

Time, A, B, C, ...

0,3.5,4.5,7.7, ...

1,2.1,6.4,8.2, ...

...

Any help is greatly appreciated. Thanks, John

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2 answers

It depends on what you mean, but yes, it should be possible. If you write more specifically what your input data and target data look like, someone can help. You can usually have sequential continuous or categorical input and sequential continuous or categorical output, or a combination thereof. I would suggest you look at the tutorials and try a few things, and then ask again here.

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Thanks. I get it now. I misunderstood the input docs: a list of input data of length T, each vector with the form [batch_size]. ''

The following link was helpful:

https://m.reddit.com/r/MachineLearning/comments/3sok8k/tensorflow_basic_rnn_example_with_variable_length/

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Source: https://habr.com/ru/post/1237253/

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