gradient_boosting_regressor loss

[MarkBusschers]

Hello,
I'm trying to define the following HyperoptEstimator:

estim = HyperoptEstimator(
regressor = gradient_boosting_regressor(
"gbr",
alpha=quantile,
loss="quantile",
n_estimators=hp.choice('n_estimators', list(np.arange(20, 80, 1, dtype=int))),
min_samples_leaf = hp.choice('min_samples', list(np.arange(10, 50, 1, dtype=int))),
max_features = hp.choice('max_features', list(np.arange(2, 10, 1, dtype=int))),
max_depth = hp.choice('max_depth', list(np.arange(2, 10, 1, dtype=int))),
min_samples_split = hp.choice('min_samples_split', list(np.arange(2, 50, 1, dtype=int))),
),
verbose=True,
algo=tpe.suggest,
max_evals=10,
trial_timeout=30,
)

This returns the folowing error:
Invalid parameter 'loss' with value 'quantile'. Choose 'squared_error', 'absolute_error', 'huber' or 'quantile'

I think the following piece of code should be changed:

@Validate(params=["loss"],
validation_test=lambda param: not isinstance(param, str) or param in ("squared_error", "absolute_error",
"huber" or "quantile"),
msg="Invalid parameter '%s' with value '%s'. "
"Choose 'squared_error', 'absolute_error', 'huber' or 'quantile'.")

To:

@Validate(params=["loss"],
validation_test=lambda param: not isinstance(param, str) or param in ("squared_error", "absolute_error",
"huber", "quantile"),
msg="Invalid parameter '%s' with value '%s'. "
"Choose 'squared_error', 'absolute_error', 'huber' or 'quantile'.")

[mandjevant]

Good catch. Thank you for reporting this.