An Accelerated Exact Algorithm for the One-Dimensional M-Variance Problem
Pattern Recognition and Image Analysis, ISSN: 1555-6212, Vol: 29, Issue: 4, Page: 573-576
2019
- 2Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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- Citations2
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- CrossRef1
Article Description
Abstract: The known quadratic NP-hard (in the strong sense) M-variance problem is considered. It arises in the following typical problem of data analysis: in a set of N objects determined by their characteristics (features), find a subset of M elements close to each other. For the one-dimensional case, an accelerated exact algorithm with complexity (Formula presented.)(N logN) is proposed.
Bibliographic Details
Pleiades Publishing Ltd
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