Wilcoxon matched pairs test (Random Forest classifier).

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書目詳細資料
主要作者:	Dávid Držík (22145693) (author)
其他作者:	Lívia Kelebercová (21864013) (author)
出版:	2025
主題:	Ecology Sociology Biological Sciences not elsewhere classified support vector machine reach statistical significance evaluated original datasets 46 %; however advanced contextual models roberta still delivered translation consistently enhanced statistically significant f1 highest absolute performance determine whether back topic classification embedding contextual word embeddings topic classification contextual embeddings roberta model roberta ). classification tasks xlink "> translated data study investigates score increasing score improvement results demonstrated modern context logistic regression less reliant language showed findings indicate especially beneficial 80 %,
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Wilcoxon matched pairs test (Random Forest classifier)<i>.</i>