Galaxy morphology in stellar light can be described by a series of ‘non-parametric’ or ‘morphometric’ parameters, such as concentration-asymmetry-smoothness, Gini, $M_{20}$, and Sérsic fit. These parameters can be applied to column density maps of atomic hydrogen (H 1). The H 1 distribution is susceptible to perturbations by environmental effects, for example, intergalactic medium pressure and tidal interactions. Therefore, H 1 morphology can potentially identify galaxies undergoing ram-pressure stripping or tidal interactions. We explore three fields in the WALLABY Pilot H 1 survey and identify perturbed galaxies based on a k-nearest neighbour (kNN) algorithm using an H 1 morphometric feature space. For training, we used labelled galaxies in the combined NGC 4808 and NGC 4636 fields with six H 1 morphometrics to train and test a kNN classifier. The kNN classification is proficient in classifying perturbed galaxies with all metrics – accuracy, precision, and recall – at 70–80%. By using the kNN method to identify perturbed galaxies in the deployment field, the NGC 5044 mosaic, we find that in most regards, the scaling relations of perturbed and unperturbed galaxies have similar distribution in the scaling relations of stellar mass versus star formation rate and the Baryonic Tully–Fisher relation, but the H 1 and stellar mass relation flatter than of the unperturbed galaxies. Our results for NGC 5044 provide a prediction for future studies on the fraction of galaxies undergoing interaction in this catalogue and to build a training sample to classify such galaxies in the full WALLABY survey.