Publication:
Classification Model for Data Streams Based on Similarity

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978-3-642-21822-4_art.pdf (4.01 MB)

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URI: https://hdl.handle.net/10433/26333
DOI: 10.1007/978-3-642-21822-4_1

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2011-07-01

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Rodríguez- Sarabia, Yanet

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Springer
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Abstract

Mining data streams is a field of study that poses new challenges. This research delves into the study of applying different techniques of classification of data streams, and carries out a comparative analysis with a proposal based on similarity; introducing a new form of management of representative data models and policies of insertion and removal, advancing also in the design of appropriate estimators to improve classification performance and updating of the model.

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Data streams,Classification,Similarity

Bibliographic reference

Mena Torres, D., Aguilar Ruiz, J., Rodríguez Sarabia, Y. (2011). Classification Model for Data Streams Based on Similarity. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6703. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21822-4_1

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