title: How to ensemble two Neural Networks that has been trained differently?
body: <p>I have created two different Neural Networks that both predict if a team is going to WIN/LOSE a hockey game. The first NN has been trained on 82 features from games that has been played. The other has been trained on 115 features from player stats in all the games that has been played.</p>
  
  <p>Some features are the same in both sets, but the important metrics differ or are represented differently (aggregated/individual)</p>
  
  <p>Is there anyway to ensemble these NNs so that it is possible to just feed it a set containing only two features like this.</p>
  
  <pre><code>h_team1   h_team_2    h_team3    a_team1   a_team2    a_team3     WIN/LOSE
     1         0           0          1          0         0
     1         0           0          0          1         0
     0         1           0          0          0         1
  </code></pre>
  
  <p>And the new NN's task will be to classify the probability of the home team winning the game.</p>
  
  <p>If I'm really off with what I'm trying to do, please correct me.</p>
  
  <p>I've added an image to help visualize the problem I'm describing. </p>
  
  <p><a href="https://imgur.com/a/ZKnGT8N" rel="nofollow noreferrer">https://imgur.com/a/ZKnGT8N</a> (The arrows point to the model I want to build, have not built it, because I do not know how)</p>
  
  <p>EDIT:</p>
  
  <p>Example data from game_DATA-set h=home a=away</p>
  
  <pre><code>h_Won/Lost h_powerPlayGoals h_powerPlayPercentage a_powerPlayGoals a_powerPlayPercentage h_team1    h_team 2     a_team1     a_team2     gameID
     1            2                    0.4                1              0.5                      1          0            1          0      1
  </code></pre>
  
  <p>Example data from player_DATA-set</p>
  
  <pre><code>Won/Lost   playerID    team1  team2   metric1   opponent1     opponent2    gameID
     1          5678       1       0     10       1              0          1
  </code></pre>