## DO NOT EDIT!
## Generated automatically from fcnntrain.cc
## by configure_make.m during package installation.

%!shared X, Y, MODEL
%! load fisheriris
%! X = meas;
%! Y = grp2idx (species);
%!error <fcnntrain: too few input arguments.> ...
%! model = fcnntrain (X, Y);
%!error <fcnntrain: too many output arguments.> ...
%! [Q, W] = fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: X must be a real numeric matrix.> ...
%! fcnntrain (complex (X), Y, 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: X must be a real numeric matrix.> ...
%! fcnntrain ({X}, Y, 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: X cannot be empty.> ...
%! fcnntrain ([], Y, 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: Y must be a real numeric matrix.> ...
%! fcnntrain (X, complex (Y), 10, 1, 0.01, [1, 1], 0.025, 50, false);
%!error <fcnntrain: Y must be a real numeric matrix.> ...
%! fcnntrain (X, {Y}, 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: Y cannot be empty.> ...
%! fcnntrain (X, [], 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: X and Y must have the same number of rows.> ...
%! fcnntrain (X, Y([1:50]), 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: labels in Y must be positive integers.> ...
%! fcnntrain (X, Y - 1, 10, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'LayerSizes' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, [10; 5], [1, 1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'LayerSizes' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, "10", [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'LayerSizes' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, {10}, [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'LayerSizes' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, complex (10), [1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'Activations' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, 10, [1; 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'Activations' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, 10, {1, 1}, 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'Activations' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, 10, "1", 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'Activations' must be a row vector of integer values.> ...
%! fcnntrain (X, Y, 10, complex ([1, 1]), 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'Activations' do not match LayerSizes.> ...
%! fcnntrain (X, Y, 10, [1, 1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: cannot have a layer of zero size.> ...
%! fcnntrain (X, Y, [10, 0, 5], [1, 1, 1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: invalid 'Activations' code.> ...
%! fcnntrain (X, Y, 10, [-1, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: invalid 'Activations' code.> ...
%! fcnntrain (X, Y, 10, [8, 1], 1, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'NumThreads' must be a positive integer scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 0, 0.01, 0.025, 50, false);
%!error <fcnntrain: 'Alpha' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, -0.01, 0.025, 50, false);
%!error <fcnntrain: 'LearningRate' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, -0.025, 50, false);
%!error <fcnntrain: 'LearningRate' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0, 50, false);
%!error <fcnntrain: 'LearningRate' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, [0.025, 0.001], 50, false);
%!error <fcnntrain: 'LearningRate' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, {0.025}, 50, false);
%!error <fcnntrain: 'Epochs' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0.025, 0, false);
%!error <fcnntrain: 'Epochs' must be a positive scalar value.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0.025, [50, 25], false);
%!error <fcnntrain: 'DisplayInfo' must be a boolean scalar.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0.025, 50, 0);
%!error <fcnntrain: 'DisplayInfo' must be a boolean scalar.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0.025, 50, 1);
%!error <fcnntrain: 'DisplayInfo' must be a boolean scalar.> ...
%! fcnntrain (X, Y, 10, [1, 1], 1, 0.01, 0.025, 50, [false, false]);
