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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