Training or using sets of explainable machine-learning modeling algorithms for predicting timing of events

A method in which one or more processing devices performs operations comprising:

• accessing training data comprising predictor data samples for a training window and response data samples for the training window, wherein (i) the predictor data samples include values of predictor variables that respectively correspond to actions performed by an entity or observations of the entity and (ii) each response data sample includes a respective outcome value of a response variable having a set of outcome values associated with the entity
• building a set of timing-prediction models from the training data, wherein building each timing-prediction model comprises training the timing-prediction model to predict a target event for a respective time bin within the training window;
• generating program code configured to (i) compute a set of probabilities for the target event by applying the set of timing-prediction models to predictor variable data and (ii) compute a time of the target event from the set of probabilities;
• and
• outputting the program code to a host computing system that is configured for modifying a host system operation based on executing the program code to compute a time of the target event.

A non-transitory computer-readable medium storing program code executable by one or more processing devices, wherein the program code, when executed by the one or more processing devices, configures the one or more processing devices to perform operations comprising:

• accessing training data comprising predictor data samples for a training window and response data samples for the training window, wherein (i) the predictor data samples include values of predictor variables that respectively correspond to actions performed by an entity or observations of the entity and (ii) each response data sample includes a respective outcome value of a response variable having a set of outcome values associated with the entity
• building a set of timing-prediction models from the training data, wherein building each timing-prediction model comprises training the timing-prediction model to predict a target event for a respective time bin within the training window;
• generating timing-prediction model code configured to (i) compute a set of probabilities for the target event by applying the set of timing-prediction models to predictor variable data and (ii) compute a time of the target event from the set of probabilities;
• and
• outputting the timing-prediction model code to a host computing system that is configured for modifying a host system operation based on executing the timing-prediction model code to compute a time of the target event.