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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)
The objective of this study is the heavy metal extraction by microemulsion, using regional vegetable oils as surfactants. Firstly, the main parameters, which have influence in the microemulsion region, such as: nature of cosurfactant, influence of cosurfactant (C)/surfactant (S) ratio and salinity were studied, with the objective of choosing the best(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)
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reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated.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)
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)