Hands-On Java Deep Learning for Computer Vision

Bias and variance

During the training of the neural network, the model may undergo various symptoms. One of them is high bias value. This leads to a high error rate on our training dataset and therefore, consecutively, a similar error on the development dataset. What this tells us is that our network has not learned how to solve the problem or to find the pattern. Graphically, we can represent the model like this:

This graph depicts senior boundaries and the errors caused by the model, where it marks the red dots as green squares and vice versa.

We may also have to worry about the high variance problem. Assume that the neural network does ...