Common Testing Issues

Below are common things to look for while test different types of models. These can be viewed in PerceptiLabs' Evaluate View.

Classification Testing

• Confusion matrix: if the confusion matrix shows that classes are mixed up, try building a more complex model.

• Table: look closely at Precision and Recall. Also, if the test accuracy is a lot worse than it is for training and validation, the model is likely overfitting.

Segmentation Testing

• Image: see Segmentation Training.

• Table: if test Dice is a lot worse than it is training and validation, the model is likely overfitting.