FLIRT
发表于 2025-3-27 00:08:13
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没血色
发表于 2025-3-27 04:27:45
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Sleep-Paralysis
发表于 2025-3-27 05:23:28
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遭受
发表于 2025-3-27 09:33:51
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同谋
发表于 2025-3-27 15:39:39
Data Science and Applications978-981-99-7814-4Series ISSN 2367-3370 Series E-ISSN 2367-3389
模仿
发表于 2025-3-27 19:39:35
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defray
发表于 2025-3-28 01:05:00
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corporate
发表于 2025-3-28 05:18:04
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Aqueous-Humor
发表于 2025-3-28 07:07:59
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做作
发表于 2025-3-28 13:31:21
An Optimized Approach for Sarcasm Detection Using Machine Learning Classifier,atasets, both sarcastic and non-sarcastic. The effectiveness of the models is evaluated in terms of several measures, including precision, accuracy, recall, and the F-measure. This paper uses logistic regression, a naive Bayes classifier, a linear support vector machine, a decision tree, and ensembl