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metrics

mae(y_true, y_pred)

Return mean absolute error (MAE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

mape(y_true, y_pred)

Return mean absolute percentage error (MAPE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

mase(y_true, y_pred, y_train, sp=1)

Return mean absolute scaled error (MASE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required
y_train DataFrame

Observed training values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

mfe(y_true, y_pred)

Return mean forecast error (MFE) AKA bias.

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

mse(y_true, y_pred)

Return mean squared error (MSE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

overforecast(y_true, y_pred)

Return total overforecast.

Overforecast (positive forecast bias) is the difference between actual and predicted for predicted values greater than actual.

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

rmse(y_true, y_pred)

Return root mean squared error (RMSE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

rmsse(y_true, y_pred, y_train, sp=1)

Return root mean squared scaled error (RMSSE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required
y_train DataFrame

Observed training values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

smape(y_true, y_pred)

Return symmetric mean absolute percentage error (sMAPE).

Use third version of SMAPE formula from https://en.wikipedia.org/wiki/Symmetric_mean_absolute_percentage_error to deal with zero division error

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

smape_original(y_true, y_pred)

Return symmetric mean absolute percentage error (sMAPE).

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

underforecast(y_true, y_pred)

Return total underforecast.

Underforecast (negative forecast bias) is the difference between actual and predicted for predicted values less than actual.

Parameters:

Name Type Description Default
y_true DataFrame

Ground truth (correct) target values.

required
y_pred DataFrame

Predicted values.

required

Returns:

Name Type Description
scores DataFrame

Score per series.

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