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Table 1: Results for the LVQ-SMOTE and MM for six (6) data sets 1The results are based on 10-fold, 1-fold or no (represented by “None”) cross validation. “None” is applicable to MM only. 2For this data set there were only three true features, i.e., Xtr has a rank of 3. 3The number of features was reduced using the FR technique. 4It was not possible to determine TP for LVQ-SMOTE from the value of the statistics reported in Nakamura et al. 5These numbers represent the sizes of the classes for the training data sets. 6The balanced data sets for LVQ-SMOTE are determined by over-sampling except in the case of Colon Cancer. 7Oversampling is not used to determine the LVQ-SMOTE because the results are not possible. |