Results of using 8 classification methods: k-nearest neighbours (kNN), k-nearest neighbours with 3 features (kNN3), naïve Bayes, support vector machines (SVM), bagged trees (BT), linear discriminant (LD), linear discriminant with 3 features (LD3) linear discriminant with 2 features (LD2) and two types of training-testing split (HO and L1O) for classifying SU and CC and results of L1O training-testing split classifying SU with and without at-risk-mental-state (CAARMS = 0 vs. CAARMS > 0). n in Testing dataset column shows number of datasets from the indicated cohort used for testing (see also the Training and testing section).
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https://figshare.com/articles/dataset/Results_of_using_8_classification_methods_k-nearest_neighbours_kNN_k-nearest_neighbours_with_3_features_kNN3_na_ve_Bayes_support_vector_machines_SVM_bagged_trees_BT_linear_discriminant_LD_linear_discriminant_with_3_features_LD3_linear_discr/24148481
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Results of using 8 classification methods: k-nearest neighbours (kNN), k-nearest neighbours with 3 features (kNN3), naïve Bayes, support vector machines (SVM), bagged trees (BT), linear discriminant (LD), linear discriminant with 3 features (LD3) linear discriminant with 2 features (LD2) and two types of training-testing split (HO and L1O) for classifying SU and CC and results of L1O training-testing split classifying SU with and without at-risk-mental-state (CAARMS = 0 vs. CAARMS > 0). n in Testing dataset column shows number of datasets from the indicated cohort used for testing (see also the Training and testing section).
创建时间：
2023-09-15
