eobox.ml.plot

eobox.ml.plot.plot_confusion_matrix(cm, class_names=None, switch_axes=False, vmin=None, vmax=None, cmap='RdBu', robust=True, logscale_color=False, fmt=',', annot_kws=None, cbar=False, mask_zeros=False, ax=None)

Plot a confusion matrix with the precision and recall added.

TODO: documentation …

TODO: check https://github.com/wcipriano/pretty-print-confusion-matrix

switch_axes if False the CM is returned as is the default of sklearn with the rows being the actual class and the columns the predicted class if True, the axis are switched.