Information Distance and Its Extensions

Li, Ming

doi:10.1007/978-3-642-24477-3_3

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“…In [27] this notation was introduced and the many results were obtained for finite nonempty multisets. A review of some of the above is [21]. …”

Section: Introductionmentioning

confidence: 99%

Normalized Compression Distance of Multisets with Applications

Cohen

Vitányi

2015

IEEE Trans. Pattern Anal. Mach. Intell.

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Pairwise normalized compression distance (NCD) is a parameter-free, feature-free, alignment-free, similarity metric based on compression. We propose an NCD of multisets that is also metric. Previously, attempts to obtain such an NCD failed. For classification purposes it is superior to the pairwise NCD in accuracy and implementation complexity. We cover the entire trajectory from theoretical underpinning to feasible practice. It is applied to biological (stem cell, organelle transport) and OCR classification questions that were earlier treated with the pairwise NCD. With the new method we achieved significantly better results. The theoretic foundation is Kolmogorov complexity.

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“…In [27] this notation was introduced and the many results were obtained for finite nonempty multisets. A review of some of the above is [21]. …”

Section: Introductionmentioning

confidence: 99%