If we decide we're interested in doing so, we could include the pipeline run train time as a field in each meta dataset record. It could be a potentially useful metalearning target. For example in an AutoML system you could have a trained metamodel which can predict the training time for a pipeline run. Then if it predicts with a high confidence that a pipeline will take much too long to train, it can decide to skip training that candidate model.
If we decide we're interested in doing so, we could include the pipeline run train time as a field in each meta dataset record. It could be a potentially useful metalearning target. For example in an AutoML system you could have a trained metamodel which can predict the training time for a pipeline run. Then if it predicts with a high confidence that a pipeline will take much too long to train, it can decide to skip training that candidate model.