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i have a dataset of 10000 event with 16 feature, and a vector of dimension 10000 that represent the label of each event; for what i understand is a classification problem but it's required to use a Lstm. How it's possible to use a RNN for a classification that doesn't involve a temporal series? And how can i implement this in the code?

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Classification can totally be done using LSTM. While this is a duplicate of another question, I can provide an example article that demonstrates how this can be done through code.

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  • $\begingroup$ thanks for your answer! i've alredy see the other question but our dataframe are different, and my problem is the input shape: how can i fed my model with my dataset n x m and my label vector? $\endgroup$
    – 2330nb111
    Commented Aug 25, 2021 at 2:42

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