… qualitative variable, the logistic regression method is used. In this study, we first introduced
the generalized maximum entropy method for a logistic regression model. A random sample …

… suggest is necessary visit the automotive maintenance center two times more than the
generalized maximum entropy model; thus, GME model reduces la frequency of inspection in the …

… The second is to generalize the maximum entropy approach. The third solution is adding
extra … A generalized maximum entropy (gme) estimation approach to fuzzy regression model. …

… entropy. We develop a flexible and consistent approach in which the estimations of
generated/attracted parameters are fuzzy with entropic membership functions. Based on a …

… fuzzy set (IFS) for modeling the uncertain decision-making problems. In this paper, a new
picture fuzzy entropy … be two PFSs on \(\Game\). We notice that E and F are different. Therefore, …

… This article explores the scope of feature extraction and maximum entropy-based fuzzy
clustering (MEFC) on eigenvalue-based cooperative spectrum sensing (CSS). The sensed …

… Spain, using generalized maximum entropy estimation, although … The resulting GME estimator
is given by (6) argmax p , w − p … techniques are needed to obtain the point estimates of the …

… to most existing techniques which treat fuzzy linear regression as an … of constructing a fuzzy
linear regression model in Bayesian … model [18], generalized maximum entropy estimation …

… the so-called neural network approach for solving ridge fuzzy regression problems, which is
… first study fuzzy regression model with crisp independent variables and LR-fuzzy dependent …

… Although approaches such as fuzzy inputs and fuzzy partitioning are used for the Gradient
… -based approach can be used to calculate also the errors (residuals) in the fuzzy regression …