How to train a RNN with LSTM cells for time series prediction : <p>I'm currently trying to build a simple model for predicting time series. The goal would be to train the model with a sequence so that the model is able to predict future values.</p>

<p>I'm using tensorflow and lstm cells to do so. The model is trained with truncated backpropagation through time. My question is how to structure the data for training.</p>

<p>For example let's assume we want to learn the given sequence:</p>

<pre><code>[1,2,3,4,5,6,7,8,9,10,11,...]
</code></pre>

<p>And we unroll the network for <code>num_steps=4</code>.</p>

<p><strong>Option 1</strong></p>

<pre><code>input data               label     
1,2,3,4                  2,3,4,5
5,6,7,8                  6,7,8,9
9,10,11,12               10,11,12,13
...
</code></pre>

<p><strong>Option 2</strong></p>

<pre><code>input data               label     
1,2,3,4                  2,3,4,5
2,3,4,5                  3,4,5,6
3,4,5,6                  4,5,6,7
...
</code></pre>

<p><strong>Option 3</strong></p>

<pre><code>input data               label     
1,2,3,4                  5
2,3,4,5                  6
3,4,5,6                  7
...
</code></pre>

<p><strong>Option 4</strong></p>

<pre><code>input data               label     
1,2,3,4                  5
5,6,7,8                  9
9,10,11,12               13
...
</code></pre>

<p>Any help would be appreciated.</p>
