Unsupervised Pattern Recognition in DATA Strams

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Khavarian, Mehrdad | 2014

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 45387 (02)
University: Sharif University of Technology
Department: Mathematical Science
Advisor(s): Zarei, Alireza
Abstract:
Pattern recognition in data streams using bounded memory and bounded time is a difficult task. There are many techniques for recognizing patterns but when we talk about data streams these algorithms became useless since there are no enough memory to store all data. In data stream model the entire data is not available at any time and we don’t have enough time processing each data.
In this thesis we consider current methods for recognizing patterns from a data streams. The goal pattern in this study was the minimum total area of k convex polygons encloses all data
Keywords:
Pattern Recognition ; Data Flow ; Clustering ; Unsupervised Learning ; Clusterhull ; Convex Hull

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