Polarity classification results for all collections with VERY-NEG lexicon, in terms of precision (Pneg), recall (Rneg) and F1neg scores for most negative (MN) and other (NMN) documents.
收藏Figshare2018-05-25 更新2026-04-29 收录
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https://figshare.com/articles/dataset/Polarity_classification_results_for_all_collections_with_VERY-NEG_lexicon_in_terms_of_precision_P_sub_i_neg_i_sub_recall_R_sub_i_neg_i_sub_and_F1_sub_i_neg_i_sub_scores_for_most_negative_MN_and_other_NMN_documents_/6357740
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资源简介：
The best F1neg for the most negative class in each dataset is highlighted (in bold).
创建时间：
2018-05-25
