1,721,250 research outputs found
Applying the possibilistic C-means algorithm in kernel-induced spaces
Full text linkIn this paper, we study a kernel extension of the classic possibilistic c-means. In the proposed extension, we implicitly map input patterns into a possibly high-dimensional space by means of positive semidefinite kernels. In this new space, we model the mapped data by means of the possibilistic clustering algorithm. We study in more detail the special case where we model the mapped data using a single cluster only, since it turns out to have many interesting properties. The modeled memberships in kernel-induced spaces yield a modeling of generic shapes in the input space. We analyze in detail the connections to one-class support vector machines and kernel density estimation, thus, suggesting that the proposed algorithm can be used in many scenarios of unsupervised learning. In the experimental part, we analyze the stability and the accuracy of the proposed algorithm on some synthetic and real datasets. The results show high stability and good performances in terms of accuracy
Tracking Time-Evolving Data Streams and an Application to Short-Term Urban Traffic Flow Forecasting
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Special Session on Bioinformatics and Biostatistics withcontributions by: P. Fariselli et al., G. Cuda et al., G. Antoniol et al., D. Malchioldi et al., C. Chennubhotla et al., A. Eleuteri et al., F. Marangoni et al., F. Masulli et al., A. Micheli et al., G. Valentini
No full textSpringer Handbook of Bio- and Neuroinformatics - Principal Editor N. Kasabov - Parts: "D (III) Modeling Regulatory Networks", "E (IV) Bioinformatics Databases and Ontologies", "F (V) Bioinformatics in Medicine, Health and Ecology", K (X) Information Modeling Brain Diseases
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Comprehensive Dictionary of Electrical Engineering - invited contribution of 50 terms on Fuzzy Sets and Systems
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