The indices used in evaluating prediction results of this component are described below.
Formula |
Description |
---|---|
\(X_{\mbox{p}}\) |
Array of predicted value. |
\(X_{\mbox{a}}\) |
Array of actual value. |
\(\mbox{mean}(X)\) |
Mean of \(X\). |
\(\mbox{median}(X)\) |
Median value in \(X\). |
\(\mbox{max}(X)\) |
Maximum value in \(X\). |
\([\cdot]_+\) |
A function which returns the argument directly if it is greater than \(0\), otherwise returns \(0\). |
Evaluation Index |
Type |
Description |
---|---|---|
root_mean_squared_error |
float |
RMSE (Root Mean Square Error), which is the square root of the mean squared error as shown below:
\(\sqrt{\mbox{mean}((X_{\mbox{p}} - X_{\mbox{a}})^2)}\)
|
root_median_squared_error |
float |
RMdSE (Root Median Square Error), which is the square root of the median squared error as shown below:
\(\sqrt{\mbox{median}((X_{\mbox{p}} - X_{\mbox{a}})^2)}\)
|
mean_abs_error |
float |
Mean of absolute error as shown below:
\(\mbox{mean}(|X_{\mbox{p}} - X_{\mbox{a}}|)\)
|
median_abs_error |
float |
Median of absolute error as shown below:
\(\mbox{median}(|X_{\mbox{p}} - X_{\mbox{a}}|)\)
|
max_abs_error |
float |
Maximum value of absolute error.
\(\mbox{max}(|X_{\mbox{p}} - X_{\mbox{a}}|)\)
|
relative_root_mean_squared_error |
float |
The square root of the mean squared relative error as shown below:
\(\sqrt{\mbox{mean}((\frac{{\large X}_{\mbox{p}} {\large - X}_{\mbox{a}}}{ {\large X}_{\mbox{a}}})^2)}\)
|
relative_root_median_squared_error |
float |
The square root of the median squared relative error as shown below:
\(\sqrt{\mbox{median}((\frac{{\large X}_{\mbox{p}} {\large - X}_{\mbox{a}}}{ {\large X}_{\mbox{a}}})^2)}\)
|
relative_mean_abs_error |
float |
The mean abs relative error as shown below:
\(\mbox{mean}(|\frac{{\large X}_{\mbox{p}} {\large - X}_{\mbox{a}}}{ {\large X}_{\mbox{a}}}|)\)
|
relative_median_abs_error |
float |
The median abs relative error as shown below:
\(\mbox{median}(|\frac{{\large X}_{\mbox{p}} {\large - X}_{\mbox{a}}}{ {\large X}_{\mbox{a}}}|)\)
|
relative_max_abs_error |
float |
The maximum abs relative error as shown below:
\(\mbox{max}(|\frac{{\large X}_{\mbox{p}} {\large - X}_{\mbox{a}}}{ {\large X}_{\mbox{a}}}|)\)
|
positive_side_root_mean_squared_error |
float |
|
positive_side_root_median_squared_error |
float |
|
positive_side_mean_abs_error |
float |
|
positive_side_median_abs_error |
float |
|
positive_side_max_abs_error |
float |
|
negative_side_root_mean_squared_error |
float |
|
negative_side_root_median_squared_error |
float |
|
negative_side_mean_abs_error |
float |
|
negative_side_median_abs_error |
float |
|
negative_side_max_abs_error |
float |
|
max_upside_err_mean_obs |
float |
Proportion of the maximum error for samples that satisfy the condition, \(X_{\mbox{p}} > X_{\mbox{a}}\) against the mean of actual values as shown below:
\(\frac{\mbox{max}({\large X}_{\mbox{p}} {\large - X}_{\mbox{a}})}{\mbox{mean}({\large X}_{\mbox{a}})}\)
|
mean_upside_err_mean_obs |
float |
Proportion of the mean error whose value is only available if it satisfies the condition, \(X_{\mbox{p}} > X_{\mbox{a}}\) (otherwise \(0\)) against the mean of actual values as shown below:
\(\frac{\mbox{mean}([{\large X}_{\mbox{p}} {\large - X}_{\mbox{a}}]_+)}{\mbox{mean}({\large X}_{\mbox{a}})}\)
|
max_downside_err_mean_obs |
float |
Proportion of the maximum error for samples that satisfy the condition, \(X_{\mbox{a}} \geq X_{\mbox{p}}\) against the mean of actual values as shown below:
\(\frac{\mbox{max}({\large X}_{\mbox{a}} {\large - X}_{\mbox{p}})}{\mbox{mean}({\large X}_{\mbox{a}})}\)
|
mean_downside_err_mean_obs |
float |
Proportion of the mean error whose value is only available if it satisfies the condition, \(X_{\mbox{a}} \geq X_{\mbox{p}}\) (otherwise \(0\)) against the mean of actual values as shown below:
\(\frac{\mbox{mean}([{\large X}_{\mbox{a}} - {\large X}_{\mbox{p}}]_+)}{\mbox{mean}({\large X}_{\mbox{a}})}\)
|
negative_pred_num |
int |
The number of the samples that satisfy the condition, \(X_{\mbox{p}} < 0\). |
std_root_mean_squared_error |
float |
|
std_root_median_squared_error |
float |
|
std_mean_abs_error |
float |
|
std_median_abs_error |
float |
|
std_max_abs_error |
float |
|
std_relative_root_mean_squared_error |
float |
|
std_relative_root_median_squared_error |
float |
|
std_relative_mean_abs_error |
float |
|
std_relative_median_abs_error |
float |
|
std_relative_max_abs_error |
float |
|
std_positive_side_root_mean_squared_error |
float |
|
std_positive_side_root_median_squared_error |
float |
|
std_positive_side_mean_abs_error |
float |
|
std_positive_side_median_abs_error |
float |
|
std_positive_side_max_abs_error |
float |
|
std_negative_side_root_mean_squared_error |
float |
|
std_negative_side_root_median_squared_error |
float |
|
std_negative_side_mean_abs_error |
float |
|
std_negative_side_median_abs_error |
float |
|
std_negative_side_max_abs_error |
float |
|
std_max_upside_err_mean_obs |
float |
|
std_mean_upside_err_mean_obs |
float |
|
std_max_downside_err_mean_obs |
float |
|
std_mean_downside_err_mean_obs |
float |
|
std_negative_pred_num |
int |
|