We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Background: The automation of many common molecular biology techniques has resulted in the accumulation of vast quantities of experimental data. One of the major challenges now fa...
Jianghui Xiong, Simon Rayner, Kunyi Luo, Yinghui L...
— In this paper, coevolution is used to evolve Artificial Neural Networks (ANN) which evaluate board positions of a two player zero-sum game (The Virus Game). The coevolved neura...
This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...