The following is a classwise evaluation index list for each target class, \(i\). Weighted averages of evaluation indices are subsequently computed wherein the weight of a target class is the proportion of the occurrences of the class in the actual population.
Evaluation Index |
Type |
Description |
---|---|---|
true_positive_<i> (**) |
int |
Number of samples determined as positive for each target class, \(i\), correctly (TP). |
false_positive_<i> (**) |
int |
Number of samples determined as positive for each target class, \(i\), incorrectly (FP). |
true_negative_<i> (**) |
int |
Number of samples determined as negative for each target class, \(i\), correctly (TN). |
false_negative_<i> (**) |
int |
Number of samples determined as negative for each target class, \(i\), incorrectly (FN). |
accuracy_<i> |
float |
Proportion of true results for each target class, \(i\), in the population as shown below:
\(\frac{\mbox{TP}_{i} + \mbox{TN}_{i}}{\mbox{TP}_{i} + \mbox{FP}_{i} + \mbox{TN}_{i} + \mbox{FN}_{i}}\)
|
classification_error_<i> |
float |
Proportion of false results for each target class, \(i\), in the population as shown below:
\(\frac{\mbox{FP}_{i} + \mbox{FN}_{i}}{\mbox{TP}_{i} + \mbox{FP}_{i} + \mbox{TN}_{i} + \mbox{FN}}_{i} = 1 - \mbox{accuracy}_{i}\)
|
precision_<i> |
float |
Proportion of the
true_positive of each target class, \(i\), against all samples determined as positive as shown below:\(\frac{\mbox{TP}_{i}}{\mbox{TP}_{i} + \mbox{FP}_{i}}\)
|
recall_<i> |
float |
Proportion of the
true_positive of each target class, \(i\), against all the actual positive samples as shown below:\(\frac{\mbox{TP}_{i}}{\mbox{TP}_{i} + \mbox{FN}_{i}}\)
|
specificity_<i> |
float |
Proportion of the
true_negative of each target class, \(i\), against all the actual negative samples as shown below:\(\frac{\mbox{TN}_{i}}{\mbox{TN}_{i} + \mbox{FP}_{i}}\)
|
false_positive_rate_<i> |
float |
Proportion of the
false_positive of each target class, \(i\), against all the actual negative samples as shown below:\(\frac{\mbox{FP}_{i}}{\mbox{TN}_{i} + \mbox{FP}_{i}} = 1 - \mbox{specificity}_{i}\)
|
false_negative_rate_<i> |
float |
Proportion of the
false_negative of each target class, \(i\), against all the actual positive samples as shown below:\(\frac{\mbox{FN}_{i}}{\mbox{TP}_{i} + \mbox{FN}_{i}} = 1 - \mbox{recall}_{i}\)
|
f_measure_<i> |
float |
Harmonic mean of
precision and recall of each target class, \(i\), as shown below:\(\frac{2 \times \mbox{precision}_{i} \times \mbox{recall}_{i}}{\mbox{precision}_{i} + \mbox{recall}_{i}}\)
|
cf_<i>_<j> (**) |
int |
Confusion matrix values that show the number of actual class, \(i\), values predicted as \(j\).
There are \(\mbox{num_target_classes}^{2}\) cf index values for every evaluation.
|
(**) Weighted average is not computed for this index.