1. The experimental study is limited: the comparisons with other methods are provided only on a single Wiki-small dataset. From that, it’s not enough to judge on the comparison with other baselines.
2. The training time seems to be the main bottleneck of the method, its training is slower than for almost any other tree method (as reported in the paper). Probably because of that, applying the method on bigger datasets becomes infeasible. (Fair to say, that the same shortcoming applies for the original Softmax Tree, and the presented method seems to double the training time).
3. The method seems to be quite sensitive to hyperparameters, so in order to apply it method for a new problem, one has to perform some careful hyperparameter search to find a proper $\alpha$.
3. The method seems to be quite sensitive to hyperparameters, so in order to apply it method for a new problem, one has to perform some careful hyperparameter search to find a proper $\alpha$.