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Discrete values have important roles in data mining and knowledge discovery. They are about intervals of numbers which are more… Expand The task of extracting knowledge from databases is quite often performed by machine learning algorithms. The majority of these… Expand We propose to perform turbulent flow simulations in such manner that the difference operators do have the same symmetry… Expand SUMMARY The paper presents an ecient numerical method for the stability analysis of linear delayed systems. The method is based… Expand In this paper we review and further develop a class of strong stability-preserving (SSP) high-order time discretizations for… Expand Discretization can turn numeric attributes into discrete ones. Feature selection can eliminate some irrelevant and/or redundant… Expand Many supervised machine learning algorithms require a discrete feature space. In this paper, we review previous work on… Expand Discretization can turn numeric attributes into discrete ones. Feature selection can eliminate some irrelevant attributes. This… Expand Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the… Expand Many classification algorithms require that the training data contain only discrete attributes. To use such an algorithm when… Expand