Classification of red blood cell shapes in flow using outlier tolerant machine learning
Fig 8
Confusion matrix with absolute values and relative percentages to evaluate the performance of the CNN approach.
The rows hereby indicate the predicted, i.e. real class, whereas the columns indicate the actual class, corresponding to the CNN output. Thus, all values on the diagonal represent the correctly classified cells.