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- 01HNFJ05PN4BD4W1J6CFYAJQPE classification P1.
- 01HNFJ05PN4BD4W1J6CFYAJQPE date "2023".
- 01HNFJ05PN4BD4W1J6CFYAJQPE language "eng".
- 01HNFJ05PN4BD4W1J6CFYAJQPE type conference.
- 01HNFJ05PN4BD4W1J6CFYAJQPE hasPart 01HNFK4Z197MANVF6DR6FVZTZE.pdf.
- 01HNFJ05PN4BD4W1J6CFYAJQPE hasPart 01HNFKN584GT00H9RASDC2E4MW.pdf.
- 01HNFJ05PN4BD4W1J6CFYAJQPE subject "Mathematics and Statistics".
- 01HNFJ05PN4BD4W1J6CFYAJQPE subject "Technology and Engineering".
- 01HNFJ05PN4BD4W1J6CFYAJQPE doi "10.1007/978-3-031-50959-9_28".
- 01HNFJ05PN4BD4W1J6CFYAJQPE isbn "9783031509582".
- 01HNFJ05PN4BD4W1J6CFYAJQPE isbn "9783031509599".
- 01HNFJ05PN4BD4W1J6CFYAJQPE issn "0302-9743".
- 01HNFJ05PN4BD4W1J6CFYAJQPE issn "1611-3349".
- 01HNFJ05PN4BD4W1J6CFYAJQPE presentedAt urn:uuid:4dc6f824-86fe-4b5e-a9c4-acfbd642b317.
- 01HNFJ05PN4BD4W1J6CFYAJQPE volume "14481".
- 01HNFJ05PN4BD4W1J6CFYAJQPE abstract "Angular Minkowski p-distance is a dissimilarity measure that is obtained by replacing Euclidean distance in the definition of cosine dissimilarity with other Minkowski p-distances. Cosine dissimilarity is frequently used with datasets containing token frequencies, and angular Minkowski p-distance may potentially be an even better choice for certain tasks. In a case study based on the 20-newsgroups dataset, we evaluate classification performance for classical weighted nearest neighbours, as well as fuzzy rough nearest neighbours. In addition, we analyse the relationship between the hyperparameter p, the dimensionality m of the dataset, the number of neighbours k, the choice of weights and the choice of classifier. We conclude that it is possible to obtain substantially higher classification performance with angular Minkowski p-distance with suitable values for p than with classical cosine dissimilarity.".
- 01HNFJ05PN4BD4W1J6CFYAJQPE author 0ECB0790-7B1F-11E8-BF84-98FB11A95AF2.
- 01HNFJ05PN4BD4W1J6CFYAJQPE author F607B454-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HNFJ05PN4BD4W1J6CFYAJQPE dateCreated "2024-01-31T10:45:55Z".
- 01HNFJ05PN4BD4W1J6CFYAJQPE dateModified "2024-11-28T00:03:11Z".
- 01HNFJ05PN4BD4W1J6CFYAJQPE editor 0ECB0790-7B1F-11E8-BF84-98FB11A95AF2.
- 01HNFJ05PN4BD4W1J6CFYAJQPE editor urn:uuid:6bf8acb4-f495-4ad9-bcd6-3a7212fc85c4.
- 01HNFJ05PN4BD4W1J6CFYAJQPE editor urn:uuid:785c58bb-1f4f-4933-9b66-f32045e3334b.
- 01HNFJ05PN4BD4W1J6CFYAJQPE editor urn:uuid:7f8711dc-2483-48aa-b2cf-cf7ea7c152f0.
- 01HNFJ05PN4BD4W1J6CFYAJQPE editor urn:uuid:bbdcf3f4-dca4-4c03-b2e2-ccd62edab86c.
- 01HNFJ05PN4BD4W1J6CFYAJQPE editor urn:uuid:e7944c11-8720-47eb-b2a9-998cd7e91a80.
- 01HNFJ05PN4BD4W1J6CFYAJQPE name "Classifying token frequencies using angular Minkowski p-distance".
- 01HNFJ05PN4BD4W1J6CFYAJQPE pagination urn:uuid:81b0d073-726b-42ce-aa71-79030df17a14.
- 01HNFJ05PN4BD4W1J6CFYAJQPE publisher urn:uuid:2c6667c3-a503-4a9b-aa17-a39195e47331.
- 01HNFJ05PN4BD4W1J6CFYAJQPE sameAs LU-01HNFJ05PN4BD4W1J6CFYAJQPE.
- 01HNFJ05PN4BD4W1J6CFYAJQPE sourceOrganization urn:uuid:813f780c-97f1-407f-91eb-65cb36314a29.
- 01HNFJ05PN4BD4W1J6CFYAJQPE type P1.