Titlebook: Learning from Imbalanced Data Sets; Alberto Fernández,Salvador García,Francisco Herrer Book 2018 Springer Nature Switzerland AG 2018 Machi

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Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreraind a flow obstacle should have a significant effect on macroscopic parameters such as recirculation length or pressure drag. In the case of a flow over a fence with laminar inflow the shear layer separating from the leading edge of the flow obstacle will undergo transition to turbulence and the mai

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Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreracale of the surrounding small-scale turbulence. Organized structures may appear as secondary flows as a result of an instability but they persist in turbulent flows. They manifest themselves as eddies or localized vortices and play an important role in e.g. mixing and transport processes. Al­ though

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Foundations on Imbalanced Classification,es in the problem. This issue is known to hinder the performance of classifiers due to their accuracy oriented design, which usually makes the minority class to be overlooked. In this chapter the foundations on the class imbalance problem are introduced. Section 2.1 gives a formal description to imb

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Performance Measures,y, the prevalence of more frequent classes may mask a poor classification performance in infrequent classes. To alleviate this problem, the choice of suitable measures is of fundamental importance. This chapter presents some performance measures that can be used to evaluate classification performanc