code: public static ClassificationDataSet loadC(Reader reader, double sparseRatio, int vectorLength) throws IOException
      {
          return loadC(reader, sparseRatio, vectorLength, DataStore.DEFAULT_STORE);
      }
docs: Loads a new classification data set from a LIBSVM file, assuming the
  label is a nominal target value
  
  @param reader the input stream for the file to load
  @param sparseRatio the fraction of non zero values to qualify a data
  point as sparse
  @param vectorLength the pre-determined length of each vector. If given a
  negative value, the largest non-zero index observed in the data will be
  used as the length.
  @param store the type of store to use for the data
  @return a classification data set
  @throws IOException if an error occurred reading the input stream