Skip to main content
Figure 4 | BMC Research Notes

Figure 4

From: Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

Figure 4

Box-plot distributions of classification accuracy (number of correct classifications/total sample size) for the 5 test samples resulting from the 5-fold cross-validation procedure (see text for abbreviations) (X2 Fr (9) = 22.211; p = 0.008). Different letters correspond to methods with statistically significant differences according to Dunn's mean rank post-hoc comparisons (p < 0.05). Circles represent outliers (observations greater than the 3rd quartile plus 1.5 times the interquartile range or smaller than the 1st quartile minus 1.5 times the interquartile range; stars represent extreme outliers, that correspond to observations greater than the 3rd quartile plus 3 times the interquartile range or smaller than the 1st quartile minus 3 times the interquartile range.

Back to article page