Data compression, data prediction, data classification, learning and data mining are all strictly related as different points of views, or instances, of the same information treatment problem. Compression inspires information theoretic tools for clustering, pattern discovery and classification. For example it has been recently proposed a new, “ blind ”, approach to clustering by compression that classifies digital objects depending on how they pair - wise compress. We will review this clustering method and we will show how this approach can be used in bio -sequences and medical images clustering.

Clustering Digital Data by Compression: Applications to Biology and Medical Images

CARPENTIERI, Bruno
2013

Abstract

Data compression, data prediction, data classification, learning and data mining are all strictly related as different points of views, or instances, of the same information treatment problem. Compression inspires information theoretic tools for clustering, pattern discovery and classification. For example it has been recently proposed a new, “ blind ”, approach to clustering by compression that classifies digital objects depending on how they pair - wise compress. We will review this clustering method and we will show how this approach can be used in bio -sequences and medical images clustering.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4250097
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