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Adding r2 score #3161

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Adding r2 score #3161

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f09c305
adding r2
sebasmos Apr 23, 2024
8a9b1e2
adding r2_square
sebasmos Apr 23, 2024
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4 changes: 3 additions & 1 deletion src/gluonts/evaluation/_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,6 +50,7 @@
quantile_loss,
smape,
num_masked_values,
r2_score
)


Expand Down Expand Up @@ -388,7 +389,7 @@ def get_base_metrics(
"MASE": mase(pred_target, median_fcst, seasonal_error),
"MAPE": mape(pred_target, median_fcst),
"sMAPE": smape(pred_target, median_fcst),
"num_masked_target_values": num_masked_values(pred_target),
"r2_score: ": smape(pred_target, median_fcst),
}

def get_metrics_per_ts(
Expand Down Expand Up @@ -504,6 +505,7 @@ def get_aggregate_metrics(
"sMAPE": "mean",
"MSIS": "mean",
"num_masked_target_values": "sum",
"r2_score":"mean",
}
if self.calculate_owa:
agg_funs["sMAPE_naive2"] = "mean"
Expand Down
16 changes: 16 additions & 0 deletions src/gluonts/evaluation/metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,22 @@
from gluonts.time_feature import get_seasonality


def r2_score(target: np.ndarray, forecast: np.ndarray) -> float:
r"""
.. math::

R^2 = 1 - \frac{SS_{res}}{SS_{tot}}

Where:
- SS_{res} = sum((Y - \hat{Y})^2)
- SS_{tot} = sum((Y - \bar{Y})^2)
"""
mean_target = np.mean(target)
ss_res = np.sum((target - forecast)**2)
ss_tot = np.sum((target - mean_target)**2)
r2 = 1 - (ss_res / ss_tot)
return r2

def calculate_seasonal_error(
past_data: np.ndarray,
freq: Optional[str] = None,
Expand Down