‘MHD25’, ‘MHD50’, ‘HD25’, ‘HD50’ datasets (e.g. ‘MC1_att’) after using the PCA algorithm. ‘MHD25’+‘HD25’ is shown in orange, and ‘MHD50’+‘HD50’ is in blue. The predicted clusters are marked with circles and crosses. The higher the percentage for each PC, the higher the relative variance in the dataset that is observed in the direction of the corresponding eigenvector (for the absolute values, see Table 3). We used n_clust = 2 in the k-means algorithm. The data is clearly separated into two distinct clusters.