Combining Soft Computing and Statistical Methods in Data Analysis by Christian Borgelt
Combining Soft Computing and Statistical Methods in Data Analysis (Advances in Intelligent and Soft Computing) by Christian Borgelt
English | Aug 10, 2010 | ISBN: 3642147453 | 639 Pages | PDF | 22 MB
English | Aug 10, 2010 | ISBN: 3642147453 | 639 Pages | PDF | 22 MB
Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002.