Body: <p>I am a beginner and I have a hard time understanding inputs and outputs of LSTM.</p>
  <p>So from the begining, I am trying to create multivariate input&amp;output LSTM for time series forecasting.
  Thankfully I've managed to operate on multivariate inputs&amp;outputs, but, what I don't understand are the indices and what is stored in them.</p>
  <p>For example, I have an intial input 2d numpy array of 4 variables:</p>
  <pre><code>a  b  c  d
  1  2  3  4
  5  6  7  8
  9 10 11 12
  </code></pre>
  <p>Lets say that the shape of this array is 5000x4 - thus 4 features and 5000 rows,
  So for the LSTM input I'd need an array of <code>x_train = (samples, timesteps, 4 features)</code>,
  And the code for input is as following:</p>
  <pre><code>   model = keras.models.Sequential([
      keras.layers.LSTM(128, return_sequences=True, input_shape=[None, 4]),
      ...
      keras.layers.Dense(4)
  ])
  </code></pre>
  <p>Also since I want 4 features as output I need 4 output neurons.</p>
  <p>Now for example my <code>y_train</code> values are in the following array:</p>
  <pre><code>y_train = (samples, timesteps, 4 features)
  </code></pre>
  <p>Now I'd like to understand in what dimension (samples, timesteps or 4 features) in x_train should be values from inital array?
  To what values timesteps dimension points, same question about samples and features.</p>
  <p>Now let's say I've trained my model, from the output and I get predictions array of the same dimensions as <code>x_train</code> and <code>y_train</code>, in what dimension are the exact predictions?
  Since I'd like to plot them or something with them?</p>
  <p>EDIT: Additional question
  What type of data should be stored in samples, timesteps, features.
  Can you give me a simple example?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-01-17T09:55:58.790Z
Comments.Text: Rather than writing "Need help understanding X and doing Y", can you please just put your **specific** question in the title?
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-01-17T10:05:16.280Z
Comments.Text: @nbro done, hope it's ok
Comments.UserDisplayName: Puchatek Kubuś
Tags: <long-short-term-memory>
Title: LSTM - What kind of data should contain every dimension of input LSTM matrix, where does specific dimension points to?
UserDisplayName: Puchatek Kubuś
ThreadText: # LSTM - What kind of data should contain every dimension of input LSTM matrix, where does specific dimension points to?
  
  (Asked by: username_0 on 2022-01-17)
  
  I am a beginner and I have a hard time understanding inputs and outputs of LSTM.
  
  So from the begining, I am trying to create multivariate input&output LSTM for time series forecasting.
  Thankfully I've managed to operate on multivariate inputs&outputs, but, what I don't understand are the indices and what is stored in them.
  
  For example, I have an intial input 2d numpy array of 4 variables:
  
  ```
  a  b  c  d
  1  2  3  4
  5  6  7  8
  9 10 11 12
  
  ```
  
  Lets say that the shape of this array is 5000x4 - thus 4 features and 5000 rows,
  So for the LSTM input I'd need an array of `x_train = (samples, timesteps, 4 features)`,
  And the code for input is as following:
  
  ```
     model = keras.models.Sequential([
      keras.layers.LSTM(128, return_sequences=True, input_shape=[None, 4]),
      ...
      keras.layers.Dense(4)
  ])
  
  ```
  
  Also since I want 4 features as output I need 4 output neurons.
  
  Now for example my `y_train` values are in the following array:
  
  ```
  y_train = (samples, timesteps, 4 features)
  
  ```
  
  Now I'd like to understand in what dimension (samples, timesteps or 4 features) in x\_train should be values from inital array?
  To what values timesteps dimension points, same question about samples and features.
  
  Now let's say I've trained my model, from the output and I get predictions array of the same dimensions as `x_train` and `y_train`, in what dimension are the exact predictions?
  Since I'd like to plot them or something with them?
  
  EDIT: Additional question
  What type of data should be stored in samples, timesteps, features.
  Can you give me a simple example?
  
  **Tags:** long-short-term-memory
  
  > **Comments:**
  > **username_1**: Rather than writing "Need help understanding X and doing Y", can you please just put your **specific** question in the title?  
  > **username_0**: @username_1 done, hope it's ok  
  
  ---
  
  ## 0 answers
  
  