title: Create vector for each column of a matrix and also construct the matrix but with that column removed
body: <p>I've imported some data from a CSV file in matlab. They are time series that are all aligned (the fact that they are time series is not important, just that each column represents a single entity, and the rows are observations for that entity). This give me say, a 2500x50 matrix of doubles called <code>data</code> and a 1x50 cell array called <code>colheaders</code>.</p>
  
  <p>What I am trying to do is use the Neural Network toolset to predict each entity (i.e., column) from all the others. The Neural Network tool takes as input a "target" (a single column of the matrix) and "input" (the original matrix but with the same column used as "target" removed from the matrix).</p>
  
  <p>Suppose the entries in <code>colheaders</code> are of the form Col1, Col2, Col3, etc. I'd like to automate the process of training the model and making predictions for each column of the original matrix so that I have as output a bunch of prediction columns labeled Predicted_Col1, Predicted_Col2, etc.</p>
  
  <p>I think I can figure out the Neural Network part but I just don't know how to begin on the matrix manipulation and cross-referencing to the <code>colheaders</code> array. This seems like a common thing to want to do so I am guessing that someone knows an easy, straight-forward way to do it that is computationally efficient. Thanks. </p>