SelectionPerformanceSingle: Selection performance (internal)

View source: R/selection_performance.R

SelectionPerformanceSingleR Documentation

Selection performance (internal)

Description

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.

Usage

SelectionPerformanceSingle(Asum, cor = NULL, thr = 0.5)

Arguments

Asum

vector (in variable selection) or matrix (in graphical modelling) containing values of 0, 1, 2 or 3.

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.

Value

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.


sharp documentation built on April 11, 2025, 5:44 p.m.