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When actually using NCD for classification, a classification algorithm has to be used. We have chosen distance to the closest examples in the set e.g. a fragment that is closest in distance to several particular instances in e.g. the exe set is classified as exe, and so on.
We have applied the generalized and universal distance measure NCD-Normalized Compression Distance-to the problem of determining the types of file fragments ...
Normalized compression distance (NCD) is a way of measuring the similarity between two objects, be it two documents, two letters, two emails, two music scores, ...
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Jan 31, 2018 · This paper investigates the usefulness of the normalized compression distance (NCD) for image similarity detection.
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Jul 20, 2021 · NCD is a way of measuring the similarity between two objects, be it two documents, two letters, two emails, two music scores, two languages, two programs, two ...
The Normalized Compression Distance (NCD) [19] is a general pur- pose method of measuring the similarity between any two arbitrary objects. The NCD works via ...
The NCD algorithm in conjunction with the k-nearest-neighbor (k ranging from one to ten) as the classification algorithm was applied to a random selection of ...
The NCD is parameter-free, feature-free, and alignment-free, and has found many applications in pattern recognition, phylogeny, clustering, and classification.
Dec 22, 2012 · Normalized compression distance (NCD) is a parameter-free, feature-free, alignment-free, similarity measure between a pair of finite objects ...
Classification algorithms that use the NCD (Normalized Compression Distance) as a similarity metric are proposed. This way of measuring similarity allows ...