منابع مشابه
Kernel ellipsoidal trimming
Ellipsoid estimation is important in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and statistical outlier or novelty detection. A new method, called Kernel Minimum Volume Covering Ellipsoid (KMVCE) estimation, that finds an ellipsoid in a kernel-defined feature space is presented. Although the method is v...
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Ellipsoid estimation is an issue of primary importance in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and novelty/outlier detection. This paper presents a new method of kernel information matrix ellipsoid estimation (KIMEE) that finds an ellipsoid in a kernel defined feature space based on a centered inf...
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A novel technique is proposed for improving the standard Vapnik-Chervonenkis (VC) dimension estimate for the Support Vector Machine (SVM) framework. The improved VC estimates are based on geometric arguments. By considering bounding ellipsoids instead of the usual bounding hyperspheres and assuming gap-tolerant classifiers, a linear classifier with a given margin is shown to shatter fewer point...
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متن کاملKPCA-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...
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ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2007
ISSN: 0167-9473
DOI: 10.1016/j.csda.2007.03.020