energy_fault_detector.anomaly_scores.rmse_score

class RMSEScore(scale=True, **kwargs)

Calculate the RMSE of given reconstruction errors.

scale: If True, mean and std of the training/fit reconstruction errors will be used to standardize recon errors during transform. Default: True

Configuration example:

train:
  anomaly_score:
    name: rmse
    params:
      scale: false

fit(x, y=None)

Calculate standard deviation and mean on training data

Parameters:

x (Union[DataFrame, ndarray]) – numpy 2d array with differences between prediction and actual sensor values
y (optional) – not used, labels indicating whether sample is normal (True) or anomalous (False).

Return type:

RMSEScore

transform(x)

Calculate the RMSE based on the deviation matrix.

Parameters:: x (Union[DataFrame, ndarray]) – numpy 2d array or pandas Dataframe with differences between prediction and actual sensor values
Return type:: Series
Returns:: RMSE for each sample.