Discussion of article "Neural networks made easy (Part 2): Network training and testing"


New article Neural networks made easy (Part 2): Network training and testing has been published:

In this second article, we will continue to study neural networks and will consider an example of using our created CNet class in Expert Advisors. We will work with two neural network models, which show similar results both in terms of training time and prediction accuracy.

The first epoch is strongly dependent on the weights of the neural network that were randomly selected at the initial stage.

After 35 epochs of training, the difference in statistics increased slightly - the regression neural network model performed better:

Value Regression neural network Classification neural network
Root mean square error 0.68 0.78
Hit percentage 12.68% 11.22%
Unrecognized fractals 20.22% 24.65%

Result of the 35th training epoch of the regression neural network (1 output neuron) Result of the 35st training epoch of the classification neural network (3 output neurons)

Testing results show that both neural network organization variants generate similar results in terms of training time and prediction accuracy. At the same time, the obtained results show that the neural network needs additional time and resources for training. If you wish to analyze the neural network learning dynamics, please check out the screenshots of each learning epoch in the attachment.

Author: Dmitriy Gizlyk