What about adding a Benchmark

What about adding a performance benchmark (by AUC and logloss) over datasets such as Criteo?

@shenweichen

@iFe1er That's a good idea,but the hyperparameters of each model are not easy to determine because it is difficult to determine a consistent setting. And it is too cumbersome to find the optimal parameters by parameter tuning. Do you have any good solution?

@shenweichen I would recommend simply adding testing them with default hyper-parameter. Control the variable such as learning rate and batch size, then compare those algorithm on the same test set. That should be helpful enough and an easy way to do.