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Finding an efficient method for sampling micro- and small-enterprises (MSEs) for research and statistical reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated. This lack of a sampling frame creates an obstacle in finding a representative sample of MSEs. This study uses computer simulations to(More)
The pursuit of unhealthy behaviors, such as smoking or binge drinking, not only carries various downside risks, but also provides pleasure. A parsimonious model, used in the literature to explain the decision to pursue an unhealthy activity, represents that decision as a tradeoff between risks and benefits. We build on this literature by surveying a rural(More)
Given the large amount of data mining algorithms, their combinations (e.g. ensembles) and possible parameter settings, finding the most adequate method to analyze a new dataset becomes an ever more challenging task. This is because in many cases testing all possibly useful alternatives quickly becomes prohibitively expensive. In this paper we propose a(More)
The problem of selecting the best classification algorithm for a specific problem continues to be very relevant, especially since the number of classification algorithms keeps growing significantly. Testing all alternatives is not really a viable option: if we compare all pairs of algorithms, as is often advocated, the number of comparisons grows(More)
Depression and other health problems are common co-morbidities among persons living with human immunodeficiency virus infection/acquired immunodeficiency syndrome (HIV/AIDS). The aim of this study was to investigate depression, health status, and substance use in relation to HIV-infected and uninfected individuals in South Africa. Using a cross-sectional(More)