/ evalml Public
When baseline score is close to 0, set percent improved to nan #1467
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In #1458 @rpeck found a dataset where, for the baseline model (which predicts the mean)
ExpVariancecame out to 0 on 2 of the 3 CV folds, but came out to ~1e-16 on the other CV fold. This resulted in the percent improvement score for
ExpVariancefor all pipelines being super big, because that computation divides by the baseline score for the objective in question.
Define a threshold (1e-10 seemed good) below which the percent improvement computation assumes the baseline objective score is essentially 0, and will then set the percent improvement for all other pipelines to nan.