期刊名称：Journal of Theoretical and Applied Computer Science
印刷版ISSN：2299-2634
电子版ISSN：2300-5653
出版年度：2012
卷号：6
期号：3
页码：21-27
出版社：Polska Akademia Nauk * Oddzial w Gdansku, Komisja Informatyki,Polish Academy of Sciences, Gdansk Branch, Computer Science Commission
摘要：This paper examines mini-models method and its effectiveness when data modelling in an information deficiency situation. It also compares the effectiveness of mini-models with var-ious methods of modelling such as neural networks, the KNN-method and polynomials. The algorithm concentrates only on local query data and does not construct a global model during the learning process when it is not necessary. It is characterized by a high efficacy and a short calculation time. The article briefly describes the method by means of four variants: linear heuristic, nonlinear heuristic, mini-models based on linear regression, and mini-models based on polynomial approximation. The paper presents the results of experiments that compare the effectiveness of mini-models with selected methods of modelling in an information deficiency situation.
关键词：mini-models; modelling; parameter of minimum number of samples; leave one out error; information gap
