A fuzzy classifier with ellipsoidal regions

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Fuzzy Classifier with Evolutionary Design of Ellipsoidal Decision Regions

A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able to adapt the distance norm to the underlying distribution of the prototype data poi...

متن کامل

KPCA-based training of a kernel fuzzy classifier with ellipsoidal regions

In a fuzzy classifier with ellipsoidal regions, a fuzzy rule, which is based on the Mahalanobis distance, is defined for each class. Then the fuzzy rules are tuned so that the recognition rate of the training data is maximized. In most cases, one fuzzy rule per one class is enough to obtain high generalization ability. But in some cases, we need to partition the class data to define more than o...

متن کامل

Robust Function Approximation Using Fuzzy Rules with Ellipsoidal Regions

This paper discusses robust function approximation when the Takagi-Sugeno type model is used for the consequent part of fuzzy rules. With this model, the parameters of the liner equation that defines the output value of the fuzzy rule are determined by the least-squares method. Therefore, if the training data include outliers, the method fails to determine the parameter values correctly. To ove...

متن کامل

Artificial Immune Classifier Based on ELLipsoidal Regions (AICELL) †

Pattern classification is a central problem in machine learning, with a wide array of applications, and rule-based classifiers are one of the most prominent approaches. Among these classifiers, Incremental Rule Learning algorithms combine the advantages of classic Pittsburg and Michigan approaches, while, on the other hand, classifiers using fuzzy membership functions often result in systems wi...

متن کامل

Generalization Improvement of a Fuzzy Classifier With Ellipsodial Regions

In a fuzzy classifier with ellipsoidal regions, each cluster is approximated by a center and a covariance matrix, and the membership function is calculated using the inverse of the covariance matrix. Thus when the number of training data is small, the covariance matrix becomes singular and the generalization ability is degraded. In this paper, during the symmetric Cholesky factorization of the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Transactions on Fuzzy Systems

سال: 1997

ISSN: 1063-6706

DOI: 10.1109/91.618273