Hello ! I have been reading the `custom_callback` function that autotvm uses to train the XGBoost cost model.
There are a few things that I would like to ask for clarification if possible: 1. The `init` function checks if the model (bst) has a `best_score` attribute which as I understand means that the model has been already trained to some degree so we set the `state` variables and we can keep doing incremental training. However since the `init` function only happens once per train at the beginning and each train restarts the model, this code has no use at least by default. Am I understanding this correctly ? The code from github: https://github.com/apache/tvm/blob/0f41d47bb43ba7509771a6254b986dcecc144479/python/tvm/autotvm/tuner/xgboost_cost_model.py#L493 2. The custom evaluation function that is generated by `xgb_average_recalln_curve_score` returns the average of N elements of the recall curve score. This N elements are the max N elements according to the `pred` values. Why dont we just average for all the elements instead ? What am I missing here ? The code from github: https://github.com/apache/tvm/blob/0f41d47bb43ba7509771a6254b986dcecc144479/python/tvm/autotvm/tuner/xgboost_cost_model.py#L614 Thanks ! --- [Visit Topic](https://discuss.tvm.apache.org/t/recall-curve-score-for-xgboost/10295/1) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/86cf6e37ef3a5a3822bff46f88ee4c53ab03340b11f2084889051278be7fe1c4).
