Some Approaches to the Model Error Problem in Data Mining Systems

In traditional methodology of statistics as well as in contemporary methodology of knowledge search in field KDD and DM the problem of object is almost completely ignored and the problem of the error of statistical model is insufficiently explored. The paper pursues several objectives. Firstly, it aims to demonstrate the significance of these two problems. Secondly, the paper intends to show that the problem of object cannot be solved within the limits of rigorous mathematical theories. The problem of model error cannot be obtained in the general case, if the error is entirely specified by means of distribution law. Thirdly, it aims to suggest a methodological analysis of new effective approaches to the mentioned problems for a number of special cases which have been developed in empirical metrological concept of statistics