Constrained Recall Objective has weird interaction with LightGBM early stopping criteria

[AndreFCruz]

Description

• When optimizing for Recall (minimizing FNR), only label positive samples are considered for computing the loss or its gradient;
• However, passing a gradient of zero for all label negatives leads to weird behavior in the GBM::Train function;
• So, for now, we're scaling down the gradient of all label negatives by multiplying them with a tiny positive number: see the label_negative_weight in ConstrainedRecallObjective::GetGradients;
  • This shouldn't be needed, but seems to temporarily fix the issue with no unintended consequences (as the gradient flowing is very small);

Reproducible example

1. Omit the else clause in ConstrainedRecallObjective::GetGradients, which deals with label negative samples, and in theory should not be needed for optimizing for recall;
2. Compile and run, and observe weird "-inf split" messages, which can lead to training stopping too early;