How to feed training set labels into Keras LSTM

Question

I’m implementing an LSTM with Keras and I know that I have to reshape the training dataset in a 3D object. Basically I have a dataset of shape (300000, 839)and I reshape it as (100000, 3, 839) because I want a timestep of 3. The question is: how could I treat the training set labels? Have I to reshape also them? if I reshape the labels to 100000, I don't truncate 200000 labels, since the starting number of labels is 300000?

Thanks in advance.

Answer 1

Your approch so far is not exactly right. Assuming you want to use the many to one approcah, the way you do it is as follows:

You have a dataset like this:

And you prepare your data in a way like this:

Source

For a timestep of 3, you discard the first 2 occurrences of your labels and use $y_{3}$ for the inputs $\{x_1, x_2,x_3\}$.

Next you don't start in $x_4$. Instead you use the next three-item slice $\{x_2, x_3, x_4\}$ with the training label $y_4$.

You continue this way until the last imput $\{x_{n-2}, x_{n-1}, x_{n}\}$ to predict $y_n$. If you have $n=30000$ samples, you can generate up to $n-2$ (29998) training samples for your model following this logic.