The indices used in evaluating prediction results of this component are described below.
Evaluation Index |
Type |
Description |
---|---|---|
true_positive |
int |
Number of samples determined as positive correctly (TP). |
false_positive |
int |
Number of samples determined as positive incorrectly (FP). |
true_negative |
int |
Number of samples determined as negative correctly (TN). |
false_negative |
int |
Number of samples determined as negative incorrectly (FN). |
accuracy |
float |
Proportion of true results in the population as shown below:
\(\frac{\mbox{TP} + \mbox{TN}}{\mbox{TP} + \mbox{FP} + \mbox{TN} + \mbox{FN}}\)
|
classification_error |
float |
Proportion of false results in the population as shown below:
\(\frac{\mbox{FP} + \mbox{FN}}{\mbox{TP} + \mbox{FP} + \mbox{TN} + \mbox{FN}} = 1 - \mbox{accuracy}\)
|
precision |
float |
Proportion of the
true_positive against all samples determined as positive as shown below:\(\frac{\mbox{TP}}{\mbox{TP} + \mbox{FP}}\)
|
recall |
float |
Proportion of the
true_positive against all the actual positive samples as shown below:\(\frac{\mbox{TP}}{\mbox{TP} + \mbox{FN}}\)
|
specificity |
float |
Proportion of the
true_negative against all the actual negative samples as shown below:\(\frac{\mbox{TN}}{\mbox{TN} + \mbox{FP}}\)
|
false_positive_rate |
float |
Proportion of the
false_positive against all the actual negative samples as shown below:\(\frac{\mbox{FP}}{\mbox{TN} + \mbox{FP}} = 1 - \mbox{specificity}\)
|
false_negative_rate |
float |
Proportion of the
false_negative against all the actual positive samples as shown below:\(\frac{\mbox{FN}}{\mbox{TP} + \mbox{FN}} = 1 - \mbox{recall}\)
|
f_measure |
float |
Harmonic mean of
precision and recall as shown below:\(\frac{2 \times \mbox{precision} \times \mbox{recall}}{\mbox{precision} + \mbox{recall}}\)
|
auc |
float |
Area under ROC (Receiver Operating Characteristic) curve. |
area_under_precision_recall |
float |
Area under PR (Precision-Recall) curve. |