To determine whether the model generalizes, alien data has been offered to the
model to see how it performs. It was shown that for similar singing styles the
models perform similar. The alien data offered containing different singing
-styles, atmospheric noise and accompaniment is classified less good.
+styles, atmospheric noise and accompaniment is classified worse.
From the results we can conclude that the model generalizes well over the
trainings set, even with little hidden nodes. The models with 3 or 5 hidden
The dataset used only contains three albums and might not be considered varied.
However, the albums are picked to represent the ends of the growling spectrum.
Therefore the resulting model can be very general. On the other side, it could
-also result in a model that is overfitted the three islands in entire space of
-grunting voices.
+also result in a model that is overfitted to the three islands in the entire
+space of grunting voices.
In this case it seems that the model generalizes well. The alien data --- similar
to the training data --- offered to the model, results in a good performance.