Overfitting problem and the over-training in the era of data: Particularly for Artificial Neural Networks
Imanol Bilbao, Javier Bilbao · 2017
When we try to classify a set of data or to create a model to a cloud of points, different techniques can be used. Among them, Artificial Neural Networks are nowadays reinvented with the peak of the Machine Learning, Big Data, etc. In the process to find the best classification and be sure on it, one of the biggest concerns that we can come up against is the problem of overfitting. In this paper, we analyze it and set out a case study.