Tree-based induction of decision list from survival data

The paper presents an algorithm for induction of decision list from survival data. The algorithm uses a survival tree as the inner learner which is repeatedly executed in order to select the best rule at each iteration. The effectiveness of the algorithm was empirical tested for two implementations of survival trees on 15 benchmark datasets. The results show that proposed algorithm for survival decision list construction is able to induce more compact models than corresponding survival tree without the loss of the accuracy of predictions.