Two lightweight ML classifiers – a decision tree and a multilayer perceptron – trained on readings from an ultrasonic sensor fail due to a dataset shift caused by the change of the train's shape. The experiment demonstrates the importance of data preprocessing and highlights the need for a critical interpretation of the models' performance metrics.