I am trying to solve the problem of sequence completion. Let's suppose we have ground truth sequence (1,2,4,7,6,8,10,12,18,20)
The input to our model is an incomplete sequence. i.e (1,2,4, _ , _ ,_,10,12,18,20). From this incomplete sequence, we want to predict the original sequence (Ground Truth sequence). Which deep learning models can be used to solve this problem?
Is this the problem of encoder-decoder LSTM architecture?
Any help is appreciated.
It is a time series problem, so it could be solved by using LSTM method. you could use Sequential Model in Keras library.
I suggest you to read the following demonstration example:
https://machinelearningmastery.com/use-different-batch-sizes-training-predicting-python-keras/
by looking at your sequence, it can be solved by RNN(recurrent neural network).
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