— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
The color reduction in digital images is an active research area in digital image processing. In many applications such as image segmentation, analysis, compression and transmissio...
Konstantinos Zagoris, Nikos Papamarkos, Ioannis Ko...
— Recently several algorithms for clustering large data sets or streaming data sets have been proposed. Most of them address the crisp case of clustering, which cannot be easily ...
This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM by introducing semi-supervised learning technique and the kernel method simultaneously into...