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The pipe of samples visualization method as base for evolutionary data discretisation

Czerniak J., Dobrosielski W.

Metody Informatyki Stosowanej

2010

nr 3 (23)

57-67

This article shows the application of the authors’ own method for visualizing multidimensionality, i.e. so called Pipe of Samples, which makes possible to visualize up to 360 dimensions. This approach constituted the base for development of evolutionary discretisation algorithm dedicated for pre-processing of data to be processed using rough sets theory. The study presents operators of crossing, mutation and selection. Structures of the algorithm data have been prepared on the basis of the aforementioned visualization so that each of the achieved individuals described one complete discretisation solution. Hence, in the proposed approach, the population is a set of many complete discretisations of all the attributes. The solution is optimized by means of evolutionary search for the optimum. The study includes results of experiments that compared LDGen adaptation algorithm with other discretisation methods used in rough sets theory. As main components of the article may be regarded such elements like visualisation method, evolutionary data discretisation method including dedicated operators and discussion on the results of experiments.

Evolutionary Approach to Data Discretization for Rough Sets Theory

Czerniak J.

Fundamenta Informaticae

2009

Vol. 92, nr 1-2

43-61

This article presents the LDGen method which is based on genetic algorithm. The author proposed evolutionary approach to the solution of the discretization problem for systems that induce rules on the basis of rough sets theory. The study describes details of the method with special focus on the crossing operator. The proposed approach concerns working with multidimensional samples. Thanks to application of the author's own method of for visualizing multidimensionality, i.e. so called Pipes of Samples, it was possible to visualize up to 360 dimensions, which is usually sufficient in case of problems the Rough Sets Theory deals with. Mutation and crossing methods were developed using this visualisation so that, for real numbers, it allowed to create individuals that describe one solution of the discretization. Hence the population is a set of many complete discretizations of all the attributes.