A fingerprint of a heterogeneous data set
نویسندگان
چکیده
Abstract In this paper, we describe the fingerprint method, a technique to classify bags of mixed-type measurements. The method was designed solve real-world industrial problem: classifying plants (individuals at higher level organisation) starting from measurements collected their production lines lower organisation). specific application, categorical information attached numerical induced simple mixture-like structures on global multivariate distributions associated with different classes. is compare mixture components given test bag corresponding classes, identifying most similar generating distribution. When compared other classification algorithms applied several synthetic data sets and original set, proposed classifier showed remarkable improvements in performance.
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ژورنال
عنوان ژورنال: Advances in data analysis and classification
سال: 2021
ISSN: ['1862-5355', '1862-5347']
DOI: https://doi.org/10.1007/s11634-021-00452-9