Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms

Ting, Kai Ming, Zhu, Ye, Carman, Mark, Zhu, Yue, Washio, Takashi and Zhou, Zhi-Hua 2019, Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms, Machine learning, vol. 108, no. 2, pp. 331-376, doi: 10.1007/s10994-018-5737-x.

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Title Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms
Author(s) Ting, Kai Ming
Zhu, YeORCID iD for Zhu, Ye orcid.org/0000-0003-4776-4932
Carman, Mark
Zhu, Yue
Washio, Takashi
Zhou, Zhi-Hua
Journal name Machine learning
Volume number 108
Issue number 2
Start page 331
End page 376
Total pages 46
Publisher Springer
Place of publication New York, N.Y.
Publication date 2019-02
ISSN 0885-6125
1573-0565
Keyword(s) nearest neighbour
distance metric
lowest probability mass neighbour
mass-based dissimilarity
classification
clustering
Language eng
DOI 10.1007/s10994-018-5737-x
Field of Research 0801 Artificial Intelligence And Image Processing
1702 Cognitive Science
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, The Author(s)
Persistent URL http://hdl.handle.net/10536/DRO/DU:30113513

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