A distance metric for ordinal data based on misclassification
Distances between data sets are used for analyses such as classification and clustering analyses. Some existing distance metrics, such as the Manhattan (City Block or L1 ) distance, are suitable for use with categorical data, where the data subtype is numeric, or more specifically, integers. Howeve...
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| Format: | Article |
| Language: | English |
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Institute of Sciences and Technology, University Center Abdelhafid Boussouf, Mila
2024-01-01
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| Series: | Journal of Innovative Applied Mathematics and Computational Sciences |
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| Online Access: | https://jiamcs.centre-univ-mila.dz/index.php/jiamcs/article/view/83 |