We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
In this paper we present a novel method for adaptation of a multi-layer perceptron neural network (MLP ANN). Nowadays, the adaptation of the ANN is usually done as an incremental r...
The main idea of a priori machine learning is to apply a machine learning method on a machine learning problem itself. We call it "a priori" because the processed data se...
Abstract. This paper introduces the application of the feature transformation approach proposed by Torkkola [1] to the domain of image processing. Thereto, we extended the approach...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...
Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...