We introduce a new ensemble method based on decision tree to discover significant and diversified rules for subtype classification of childhood acute lymphoblastic leukemia, a ...
Several challenging new applications demand the ability to do data mining on resource constrained devices. One such application is that of monitoring physiological data streams ob...
Abstract. Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target ...
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzerosk...
Multi-ported memories are challenging to implement with FPGAs since the provided block RAMs typically have only two ports. We present a thorough exploration of the design space of...
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...