BACKGROUND The purpose of this study was to examine the impact of combined cardiorespiratory fitness and waist-to-height ratio in the form of a fit-fat index on incident diabetes risk. Additionally, the independent predictive performance of cardiorespiratory fitness, waist-to-height ratio, and body mass index also were estimated and compared. METHODS This was a prospective cohort study of 10,...

With the financial crises ongoing in Greece and Venezuela, sovereign debt crises have become more and more prominent in the public eye. Thus, it has become important to be able to predict when nations will enter such debt crises. We collected publicly available data in order to train models to predict, given a nation’s economic status in one year, whether they would be in a debt crisis the next...

We consider the random walk among random conductances on Z. We assume that the conductances are independent, identically distributed and uniformly bounded away from 0 and infinity. We obtain a quantitative version of the central limit theorem for this random walk, which takes the form of a Berry-Esseen estimate with speed t−1/10 for d 6 2, and speed t−1/5 for d > 3, up to logarithmic corrections.

In this work we study variable-significance in classification using the Random Forest proximity matrix and local Importance matrix. We use the proximity m atrix t o g roup t he s amples acr oss a number of c lusters a nd use t hese clusters to s tratify th e importance of a variable. We apply t his a pproach t o a cardiovascular g enotype d ataset f or sample classification b ased o n coronary ...

Financial crime is a rampant but hidden threat. In spite of this, predictive policing systems disproportionately target “street crime” rather than white collar crime. This paper presents the White Collar Crime Early Warning System (WCCEWS), a white collar crime predictive model that uses random forest classifiers to identify high risk zones for incidents of financial crime.

We describe a method for human parsing that is straightforward and competes with state-of-the-art performance on standard datasets. Unlike the state-of-the-art, our method does not search for individual body parts or poselets. Instead, a regression forest is used to predict a body configuration in body-space. The output of this regression forest is then combined in a novel way. Instead of avera...

Automatic recognition of multiple musical instruments in polyphonic and polytimbral music is a difficult task, but often attempted to perform by MIR researchers recently. In papers published so far, the proposed systems were validated mainly on audio data obtained through mixing of isolated sounds of musical instruments. This paper tests recognition of instruments in real recordings, using a re...

Studying the geometry generated by Gaussian and Gaussianrelated random fields via their excursion sets is now a well developed and well understood subject. The purely non-Gaussian scenario has, however, not been studied at all. In this paper we look at three classes of stable random fields, and obtain asymptotic formulae for the mean values of various geometric characteristics of their excursio...