Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
In many application fields, huge binary datasets modeling real life-phenomena are daily produced. The dataset records are usually associated with observations of some events, and...
In this paper, we experimentally evaluated the effect of outlier detection methods to improve the prediction performance of fault-proneness models. Detected outliers were removed ...
Background: Microarray experiments, as well as other genomic analyses, often result in large gene sets containing up to several hundred genes. The biological significance of such ...
Jason S. M. Lee, Gurpreet Katari, Ravi Sachidanand...
In this paper we present a methodology supporting the definition of data models on basis of a limited set of well-known UML features, thereby allowing these models to be created an...