    Data Pre-Processing

 
  1. Time Series Training Data File Creation:
     Given a file which will store the generated training data and 
     a file of flat time series data, in which each
     row corresponds to a different time, the program
   a. Asks the user how many days does the user want to used for forcasting
     and how many days does the user want to forcast, i.e. which row and column
     elements correspond to inputs and outputs, 
   b. Slides a window down the file and writes inputs and desired
      outputs to a training or testing data file.
  
  2. Data Compression:
     This program performs the forward or inverse Karhunen Loeve 
     transform (KLT) in order to
   a. Compress the input or desired output vectors in a 
      training data file so that redundancy is reduced and
      smaller networks can be trained,
   b. Expand or inverse transform a file containing network 
      output vectors, so that these vectors are the same size 
      as the original uncompressed desired output vectors.
  
 3. Feature Selection:
     This program analyzes a training data file for classification 
     or mapping and
   a. Prints out a list of feature numbers and numbers denoting importance.
      Larger values of the measure denote more importance
   b. Orders the features according to their importance
 
 4. For information on file formats for this package, see "File Formats"
     under main menu "Help".


