# Assuming you have a confusion matrix stored in the variable "conf_matrix"
# Calculate accuracy
accuracy <- sum(diag(conf_matrix)) / sum(conf_matrix)
# Calculate error rate
error_rate <- 1 - accuracy
# Calculate sensitivity (true positive rate)
sensitivity <- conf_matrix[2, 2] / sum(conf_matrix[2, ])
# Calculate specificity (true negative rate)
specificity <- conf_matrix[1, 1] / sum(conf_matrix[1, ])
# Calculate precision (positive predictive value)
precision <- conf_matrix[2, 2] / sum(conf_matrix[, 2])
# Calculate F1 score
f1_score <- 2 (precision sensitivity) / (precision + sensitivity)
# Create a performance matrix
performance_matrix <- matrix(c(accuracy, error_rate, sensitivity, specificity, precision, f1_score), nrow = 1, byrow = TRUE)
colnames(performance_matrix) <- c("Accuracy", "Error Rate", "Sensitivity", "Specificity", "Precision", "F1 Score")