Neural Networks

For this activity, we did another image classification based on neural networks. A neural network consists of 3 parts, an input layer, where in our case contains the features of an object class, a hidden layer, where the features are compared, and an output layer, which gives what class the object belongs. The output of the neural network I made is either 0(class 1) or 1(class 2) depending on what class the object belongs.
For comparison with other techniques, I used the same data as the previous activities(probabilistic classification and pattern recognition).
For this method, I also obtained a 100% correct classification.

Program Output:
0.0000048 0.0000250 0.0002727 0.0351369
0.9999835 0.999997 0.9999921 0.9684366
Rounding this numbers off gives 0 for the first 4 test and 1 for the next 4 which is correct since the first 4 images were taken from class 1 and the others from class 2.
//Scilab code
//4 neurons in the input layer, 32 in the hidden layer and 1 in the ouput layer
N = [4,32,1];

// Training Set
x = [3730,0.526882,0.475084,0.394192;
4277,0.630000,0.455594,0.388616;
4181,0.656250,0.462898,0.386272;
4262,0.744186,0.479152,0.397529;
3876,0.868421,0.564352,0.331341;
3576,0.888889,0.522656,0.339387;
3754,0.893333,0.525226,0.349733;
4161,0.802469,0.503910,0.352362]';
normalizer = max(x(1,:)); //to reduce the magnitude of the area
x(1, :) = x(1, :)./normalizer;
t = [0 0 0 0 1 1 1 1];
lp = [2.5,0];
W = ann_FF_init(N);
//Training cyles
T = 1000;
W = ann_FF_Std_online(x,t,N,W,lp,T);
//x is the training t is the output W is the initialized weights,
//N is the NN architecture, lp is the learning rate and T is the number of iterations

test = [3730,0.526882,0.475084,0.394192;
4277,0.630000,0.455594,0.388616;
4181,0.656250,0.462898,0.386272;
4262,0.744186,0.479152,0.397529;
3876,0.868421,0.564352,0.331341;
3576,0.888889,0.522656,0.339387;
3754,0.893333,0.525226,0.349733;
4161,0.802469,0.503910,0.352362]';
test(1, :) = test(1, :)./normalizer;
ann_FF_run(test,N,W)
//Code end

I give myself a grade of 10 since I was able to correctly use and modify the given program.