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Fig. 4 | BMC Bioinformatics

Fig. 4

From: Towards a supervised classification of neocortical interneuron morphologies

Fig. 4

Effects of under- and over-sampling the full dataset with the chosen rates. Each bar represents a one-versus-all classification task (e.g., the leftmost bar is for ChC versus rest). ‘Positive‘ denotes the examples of the class of interest (e.g., ChC in the leftmost bar), ‘Synthetic‘ are the artificial SMOTE examples of the positive class (i.e., the class of interest), while ‘Negative‘ are the kept examples of all remaining classes. The horizontal line shows the size of the original data set (217 examples). For ChC (leftmost bar), for example, applying our sampling method to the full data set containing seven ChC cells (red segment of the bar), would retain 105 (blue segment) out of 210 non-ChC cells and add 14 synthetic ChC cells (green segment), yielding a data set of size 126 (hence the bar is lower than the horizontal line at 217). Except for BA, in all cases the class of interest was the minority class. For BA we performed no undersampling

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