cal.F1Score {GAGAs}

Calculate F1 score for classification, the inputs must be characters, and each of these elements must be either 'FALSE' or 'TRUE'.

Description

Calculate F1 score for classification, the inputs must be characters, and each of these elements must be either 'FALSE' or 'TRUE'.

Usage

cal.F1Score(predictions, truelabels)

Arguments

predictions

predictions

truelabels

true labels

Value

F1 score

Examples

set.seed(2022)
p_size = 30
sample_size=300
R1 = 3
R2 = 2
ratio = 0.5 #The ratio of zeroes in coefficients
# Set the true coefficients
zeroNum = round(ratio*p_size)
ind = sample(1:p_size,zeroNum)
beta_true = runif(p_size,0,R2)
beta_true[ind] = 0
X = R1*matrix(rnorm(sample_size * p_size), ncol = p_size)
y=X%*%beta_true + rnorm(sample_size,mean=0,sd=2)
# Estimation
fit = GAGAs(X,y,alpha = 3,family="gaussian")
Eb = fit$beta
cat("\n F1 score:", cal.F1Score(as.character(Eb!=0),as.character(beta_true!=0)))