برازش و انتخاب متغیر در رگرسیون خطی چند فازی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|24204||2006||21 صفحه PDF||سفارش دهید||9825 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Fuzzy Sets and Systems, Volume 157, Issue 19, 1 October 2006, Pages 2627–2647
In performing a fuzzy multiple linear regression model, important topics are: to measure the fitting quality of the model and to find the “best” set of input variables that explain the variation in the observed system responses. In this paper, by considering an exploratory approach, to express the quality of fit of a fuzzy linear regression model, a coefficient of multiple determination R2R2 for symmetrical fuzzy variable has been suggested. Furthermore, for overcoming the inconveniences of R2R2 an adjusted version of R2R2 (denoted by View the MathML sourceR¯2) has been defined. For measuring the fitting performances of the estimated model, a fuzzy extension of another goodness of fit measure, the so-called Mallows index (Cp)(Cp), has been considered. All the proposed fitting measures have been utilized for selecting suitably the input variables of a fuzzy linear regression model. To this purpose, some variable selection procedures based on R2R2, View the MathML sourceR¯2 and CpCp have been suitably extended in a fuzzy framework. To explain the efficacy of the goodness of fit measures and the variable selection criteria some examples are also shown.