common_stats¶
Variables
-
struct [anonymous] get_classes¶
Get the array of classes.
- Param lbl_true
array of true labels as integers
- Param lbl_pred
array of predicted labels as integers
- Param n_true
size of lbl_true array
- Param n_pred
size of lbl_pred array
- Return
Vector of classes found
-
struct [anonymous] get_confusion_matrix¶
Get the confusion matrix of the labels.
A confusion matrix, also known as an error matrix, is a specific table layout that allows visualization of the performance of an algorithm.
- Param lbl_true
array of true labels as integers
- Param lbl_pred
array of predicted labels as integers
- Param n_lbl
size of label arrays
- Param classes
array of classes
- Param Nclass
size of classes array (aka number of classes)
- Return
The confusion matrix as ravel array
-
struct [anonymous] get_TP¶
Get the True positive score.
A true positive test result is one that detects the condition when the condition is present (correctly identified).
- Param confusion_matrix
the confusion matrix of the labels
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of True positive scores (lenght := Nclass)
-
struct [anonymous] get_FN¶
Get the False negative score.
A false negative test result is one that does not detect the condition when the condition is present (incorrectly rejected).
- Param confusion_matrix
the confusion matrix of the labels
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of False negative scores (lenght := Nclass)
-
struct [anonymous] get_FP¶
Get the False positive score.
A false positive test result is one that detects the condition when the condition is absent (incorrectly identified).
- Param confusion_matrix
the confusion matrix of the labels
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of False positive scores (lenght := Nclass)
-
struct [anonymous] get_TN¶
Get the True negative score.
A true negative test result is one that does not detect the condition when the condition is absent (correctly rejected).
- Param confusion_matrix
the confusion matrix of the labels
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of True negative scores (lenght := Nclass)
-
struct [anonymous] get_POP¶
Get the Total sample size.
POP = TP + TN + FN + FP
- Param TP
array of true positives
- Param TN
array of true negatives
- Param FP
array of false positives
- Param FN
array of false negative
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of total samples for each class.
-
struct [anonymous] get_P¶
Number of positive samples.
Also known as support (the number of occurrences of each class in y_true).
P = TP + FN
- Param TP
array of true positives
- Param FN
array of false negative
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of the number of positive samples for each class.
-
struct [anonymous] get_N¶
Number of negative samples.
N = TN + FP
- Param TN
array of true negatives
- Param FP
array of false positives
- Param Nclass
size of classes array (aka number of classes)
- Return
The array of the number of negative samples for each class