title: NN multidim regression with matrix as output
body: <p>I want to build a simple NN for regression purposes; the dimension of my input data reads (100000,3): meaning I have 1mio particles and their corresponding x,y,z coordinates. Out of these particles I want to predict centers which the particles correspond to where the data of the centers read (1000,3).</p>
  
  <p>my question is: since the input array should have the same number of samples as target arrays how can I solve this problem?</p>
  
  <p>actually my mapping is from (100000,3) -> (1000,3) because on average about 100 particles belong to one center.</p>
  
  <p>to train the model i will use many of those datasets with the right centers as output; after that i want to predict out of one new set of particle coordinates the corresponding centers.</p>