In one embodiment, an edge computing device for performing decision tree training and inference includes interface circuitry and processing circuitry. The interface circuitry receives training data and inference data that is captured, at least partially, by sensor(s). The training data corresponds to a plurality of labeled instances of a feature set, and the inference data corresponds to an unlabeled instance of the feature set. The processing circuitry: computes a set of feature value checkpoints that indicate, for each feature of the feature set, a subset of potential feature values to be evaluated for splitting tree nodes of a decision tree model; trains the decision tree model based on the training data and the set of feature value checkpoints; and performs inference using the decision tree model to predict a target variable for the unlabeled instance of the feature set.