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[BUG] pass user passed parameters to ForecastX to underlying estimators #4391

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merged 5 commits into from Mar 26, 2023
Merged

[BUG] pass user passed parameters to ForecastX to underlying estimators #4391

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3d90f4c
add to list of contributors
yarnabrina Mar 25, 2023
8839818
use `coverage` parameter for `predict_interval`
yarnabrina Mar 25, 2023
d777508
use `alpha` parameter for `predict_quantiles`
yarnabrina Mar 25, 2023
7713388
use `cov` and `marginal` parameters
yarnabrina Mar 25, 2023
461a0bf
Merge branch 'main' into pr/4391
fkiraly Mar 25, 2023
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9 changes: 9 additions & 0 deletions .all-contributorsrc
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Expand Up @@ -2136,6 +2136,15 @@
"code",
"maintenance"
]
},
{
"login": "yarnabrina",
"name": "Anirban Ray",
"avatar_url": "https://avatars.githubusercontent.com/u/39331844?v=4",
"profile": "https://github.com/yarnabrina/",
"contributions": [
"bug"
]
}
]
}
8 changes: 4 additions & 4 deletions sktime/forecasting/compose/_pipeline.py
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Expand Up @@ -1416,7 +1416,7 @@ def _predict_interval(self, fh, X=None, coverage=0.90):
quantile forecasts at alpha = 0.5 - c/2, 0.5 + c/2 for c in coverage.
"""
X = self._get_forecaster_X_prediction(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_interval(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_interval(fh=fh, X=X, coverage=coverage)
return y_pred

def _predict_quantiles(self, fh, X, alpha):
Expand Down Expand Up @@ -1446,7 +1446,7 @@ def _predict_quantiles(self, fh, X, alpha):
at quantile probability in second col index, for the row index.
"""
X = self._get_forecaster_X_prediction(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_quantiles(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_quantiles(fh=fh, X=X, alpha=alpha)
return y_pred

def _predict_var(self, fh=None, X=None, cov=False):
Expand Down Expand Up @@ -1486,7 +1486,7 @@ def _predict_var(self, fh=None, X=None, cov=False):
Note: no covariance forecasts are returned between different variables.
"""
X = self._get_forecaster_X_prediction(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_var(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_var(fh=fh, X=X, cov=cov)
return y_pred

# todo: does not work properly for multivariate or hierarchical
Expand Down Expand Up @@ -1524,7 +1524,7 @@ def _predict_proba(self, fh, X, marginal=True, legacy_interface=None):
"""
X = self._get_forecaster_X_prediction(fh=fh, X=X)
y_pred = self.forecaster_y_.predict_proba(
fh=fh, X=X, legacy_interface=legacy_interface
fh=fh, X=X, marginal=marginal, legacy_interface=legacy_interface
)
return y_pred

Expand Down