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A survey of distance measures for mixed variables
International Journal of Chemical Studies · 2020 · Vol. 8(4) · pp. 338–343
Sudha Bishnoi✉(Chaudhary Charan Singh Haryana Agricultural University)BK Hooda(Chaudhary Charan Singh Haryana Agricultural University)
Abstract
Distance measures are base for many statistical and data science methods with their applicability in various fields of science. Mixed variables data which is combination of continuous and categorical variables occurs frequently in fields such as medical, agriculture, remote sensing, biology, marketing, ecology etc., but a little work has been done for evaluating distance for such type of data. As there is not much literature available on distance measures for mixed data, therefore the fundamental sources that provide a comprehensive detail of a particular measure for mixed variables data were studied and reviewed in this paper.
Bayesian Methods and Mixture ModelsStatistical Methods and InferenceAdvanced Clustering Algorithms ResearchCategorical variableMeasure (data warehouse)Distance measuresVariablesStatisticsMixed modelContinuous variableComputer scienceMathematicsEconometrics
Citations
11
FWCI
0.69
field-weighted impact
References
22
Percentile
77%
vs. same field & year
Citations per year
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A survey of distance measures for mixed variables
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