Methods of data sample metrics evaluation based on fractal dimension for computational intelligence model buiding

The problem of subsample selection for the model building on the precedents is addressed in the paper. The sequential and parallel methods of data sample metrics evaluation are proposed. They are based on the principles of fractal dimension and allow to characterize sample properties important for classification. The developed methods have been implemented in software and used for solving the problems of classification.