Fuzzy clustering with the generalized entropy of feature weights
نویسندگان
چکیده
منابع مشابه
Fuzzy clustering with the generalized entropy of feature weights
Fuzzy c-means (FCM) is an important clustering algorithm. However, it does not consider the impact of different feature on clustering. In this paper, we present a fuzzy clustering algorithm with the generalized entropy of feature weights FCM (GEWFCM). By introducing feature weights and adding regularized term of their generalized entropy, a new objective function is proposed in terms of objecti...
متن کاملEnsemble Of Image Segmentation With Generalized Entropy Based Fuzzy Clustering
Ensemble of image segmentation based on generalized entropy’s fuzzy clustering is studied in this paper. Aiming at the generalized entropy’s objective function in fuzzy clustering and introducing the spatial information into this objective function, we obtain an image segmentation algorithm ISGFCM based on neural network. Further, we introduce kernel into above objective function to obtain its ...
متن کاملImage Segmentation with Fuzzy Clustering Based on Generalized Entropy
Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to impro...
متن کاملA Weighted Sample’s Fuzzy Clustering Algorithm With Generalized Entropy
Combined with weight of samples and kernel function, fuzzy clustering method with generalized entropy is studied. Objective function for fuzzy clustering with generalized entropy based on sample weighting is obtained. Following that, fuzzy clustering algorithm with generalized entropy based on sample weighting is presented. In addition, by introducing kernel into the presented objective functio...
متن کاملFuzzy Entropy Clustering
The well-known generalisation of hard Cmeans (HCM) clustering is fuzzy C-means (FCM) clustering where a weight exponent on each fuzzy membership is introduced as the degree of fuzziness. An alternative generalisation of HCM clustering is proposed in this paper. This is called fuzzy entropy (FE) clustering where a weight factor of the fuzzy entropy function is introduced as the degree of fuzzy e...
متن کاملذخیره 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: International Journal of Advanced Computer Research
سال: 2016
ISSN: 2249-7277,2277-7970
DOI: 10.19101/ijacr.2016.627010