Many algorithms in decision tree learning have not been designed to handle numerically-valued attributes very well. Therefore, discretization of the continuous feature space has to be carried out. In this article we introduce the concept of cost-sensitive discretization as a preprocessing step to induction of a classifier and as an elaboration of the error-based discretization method to obtain ...

In order to perform numerical simulations of the Kardar-Parisi-Zhang (KPZ) equation, in any dimensionality, a spatial discretization scheme must be prescribed. The known fact that the KPZ equation can be obtained as a result of a Hopf-Cole transformation applied to a diffusion equation (with multiplicative noise) is shown here to strongly restrict the arbitrariness in the choice of spatial disc...

investigating nozzle’s orifice flow is challenging both experimentally and theoretically. this paper focuses on simulating flow inside diesel injector nozzle via ansys fluent v15. validation is performed with experimental results from winkhofler et al (2001). several important parameters such as mass flow rate, velocity profiles and pressure profiles are used for this validation. results includ...

in chemical engineering, several processes are represented by singular boundary value problems. in general, classical numerical methods fail to produce good approximations for the singular boundary value problems. in this paper, chebyshev finite difference (chfd) method and dtm-pad´e method, which is a combination of differential transform method (dtm) and pad´e approximant, are applied for sol...

This study attempts to identify the merits of six of the most popular discretization methods when confronted with a randomly generated dataset consisting of attributes that conform to one of eight common statistical distributions. It is hoped that the analysis will enlighten as to a heuristic which identifies the most appropriate discretization method to be applied, given some preliminary analy...

Many algorithms in decision tree learning are not designed to handle numeric valued attributes very well. Therefore, discretization of the continuous feature space has to be carried out. In this article we introduce the concept of cost sensitive discretization as a preprocessing step to induction of a classifier and as an elaboration of the error-based discretization method to obtain an optimal...

Page 2 of 46 Abstract The area of Knowledge discovery and Data mining is growing rapidly. A large number of methods is employed to mine knowledge. Several of the methods rely of discrete data. However, most datasets used in real application have attributes with continuously values. To make the data mining techniques useful for such datasets, discretization is performed as a preprocessing step o...

Abstract. Bridges and Reich suggested the idea of multi-symplectic spectral discretization on Fourier space [4]. Based on their theory, we investigate the multi-symplectic Fourier pseudospectral discretization of the nonlinear Schrödinger equation (NLS) on real space. We show that the multi-symplectic semi-discretization of the nonlinear Schrödinger equation with periodic boundary conditions ha...