Water Balance: Abstaining from Obtaining While Retaining

Filtering Large Propositional Rule Sets While Retaining Classifier Performance

Data mining is the problem of inducing models from data. Models have both a descriptive and a predictive aspect. Descriptive models can be inspected and used for knowledge discovery. Models consisting of decision rules – such as those produced by methods from Pawlak’s rough set theory – are in principle descriptive, but in practice the induced models are too large to be inspected. In this thesi...

Retaining Antiviral Immune Competence Protects from Autoimmune Diabetes While Disruption of the STAT4 Signaling Pathway

Aggregating Forecasts of Chance from Incoherent and Abstaining Experts

Linear averaging is a popular method for combining forecasts of chance, but it is of limited use in the context of incoherent or abstaining judges. Recently proposed, the coherent approximation principle (CAP) generalizes linear averaging to have wider applicability yet suffers from computational intractability in cases of interest. This paper proposes a unified framework that views CAP and lin...

On Abstaining Classifiers

Contrary to standard non-abstaining classifiers, abstaining classifiers have the choice to label an instance with any of the given class labels or to refrain from giving a classification in order to improve predictive performance. Our interest in abstaining classifiers is motivated by applications for which reliable predictions can only be obtained for a fraction of instances such as, for examp...

Translocation of uranium from water to foodstuff while cooking.

The present work report the unusual uranium uptake by foodstuff, especially those rich in carbohydrates like rice when they are cooked in water, contaminated with uranium. The major staple diet in South Asia, rice, was chosen to study its interaction with UO2(2+), the active uranium species in water, using inductively coupled plasma mass spectrometry. Highest uptake limit was checked by cooking...