Ensemble: A Tool for Performance Modeling of Applications in Cloud Data Centers

An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any ...

Combining the results of a number of individually trained classification systems to obtain a more accurate classifier is a widely used technique in pattern recognition. In this article, we have introduced a rough set based meta classifier (RSM). ...

In object-oriented software development, a plethora of studies have been carried out to present the application of machine learning algorithms for fault prediction. Furthermore, it has been empirically validated that an ensemble method can improve ...