View source: R/selection_performance.R
SelectionPerformanceSingle | R Documentation |
Computes different metrics of selection performance from a categorical vector/matrix with 3 for True Positive, 2 for False Negative, 1 for False Positive and 0 for True Negative.
SelectionPerformanceSingle(Asum, cor = NULL, thr = 0.5)
Asum |
vector (in variable selection) or matrix (in graphical modelling)
containing values of |
cor |
optional correlation matrix. Only used in graphical modelling. |
thr |
optional threshold in correlation. Only used in graphical modelling and when argument "cor" is not NULL. |
A matrix of selection metrics including:
TP |
number of True Positives (TP) |
FN |
number of False Negatives (TN) |
FP |
number of False Positives (FP) |
TN |
number of True Negatives (TN) |
sensitivity |
sensitivity, i.e. TP/(TP+FN) |
specificity |
specificity, i.e. TN/(TN+FP) |
accuracy |
accuracy, i.e. (TP+TN)/(TP+TN+FP+FN) |
precision |
precision (p), i.e. TP/(TP+FP) |
recall |
recall (r), i.e. TP/(TP+FN) |
F1_score |
F1-score, i.e. 2*p*r/(p+r) |
If argument "cor" is provided, the number of False Positives among correlated (FP_c) and uncorrelated (FP_i) pairs, defined as having correlations (provided in "cor") above or below the threshold "thr", are also reported.
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