How To Set Up Lstm Network For Predict Multi-sequence?

I am learning how to set up the RNN-LSTM network for prediction. I have created the dataset with one input variable. x y 1 2.5 2 6 3 8.6 4 11.2 5 13.8 6 16.4 ... By the fol

Solution 1:

Q1. Units in LSTM is the number of neurons in your LSTM layer.

Q2. That depends on your model / data. Try changing them around to see the effect.

Q3. That depends which apporach you take.

Q4. Ideally you'll want to predict a single time step every time. It is possible to predict several at a time, but in my experience you will get better results like as i have described below

e.g

use y(t-1), y(t) to predict y_hat(t+1)

THEN

use y(t), y_hat(t+1) to predict y_hat(t+2)

Are you sure you're actually using X to predict Y in this case? how does train x/y and test x/y look like?

Solution 2:

Re Q1: It is the number of LSTM cells (=LSTM units), which consist of several neurons themselves but have (in the standard case as given) only one output each. Thus, the number of units corresponds directly to the dimensionality of your output.