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Evaluation of multiple classification models including Support Vector Machine (SVM), Random Forest (RF), naïve Bayes (Bayes), Neural Network (NNT), K-Nearest Neighbor (KNN) and Logistic regression models via 10-fold cross-validation (10FCV).

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Figshare2015-12-02 更新2026-04-29 收录
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https://figshare.com/articles/dataset/_Evaluation_of_multiple_classification_models_including_Support_Vector_Machine_SVM_Random_Forest_RF_na_239_ve_Bayes_Bayes_Neural_Network_NNT_K_Nearest_Neighbor_KNN_and_Logistic_regression_models_via_10_fold_cross_validation_10FCV_/1058093
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Evaluation of multiple classification models including Support Vector Machine (SVM), Random Forest (RF), naïve Bayes (Bayes), Neural Network (NNT), K-Nearest Neighbor (KNN) and Logistic regression models via 10-fold cross-validation (10FCV).
创建时间:
2015-12-02
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