Data set overview.

Overview of the five real-world data sets and their basic characteristics: n is the number of classes, m is the number of features or, in other words, the dimension of the feature space , I is the total number of datapoints, and D is the number of training datapoints. The number T of test datapoints is just T ≔ I − D. We abbreviate the references as a) [25], b) [26], c) [27], d) [28], e) [29], f) [30], g) [2], and h) [31]. Also, we turned the originally multi-class data set pine into a binary problem as described in [2].