1. An apparatus comprising: a multi-task machine learning component for learning a set of tasks comprising two or more different tasks based on a set of examples wherein the examples are represented by features of a set of features, the multi-task machine learning component comprising a digital processing device configured to learn an ensemble of base rules wherein each base rule is learned for a sub-set of the set of features and comprises a multi-task decision tree (MT-DT) having nodes comprising decision rules for tasks of the set of tasks; and an inference component comprising a digital processing device configured to predict a result for at least one task of the set of tasks for an input item represented by features of the set of features using the learned ensemble of base rules.