bnns (version 0.1.2)

measure_bin: Measure Performance for Binary Classification Models

Description

Evaluates the performance of a binary classification model using a confusion matrix and accuracy.

Usage

measure_bin(obs, pred, cut = 0.5)

Value

A list containing:

conf_mat

A confusion matrix comparing observed and predicted class labels.

accuracy

The proportion of correct predictions.

ROC

ROC generated using pROC::roc

AUC

Area under the ROC curve.

Arguments

obs

A numeric or integer vector of observed binary class labels (0 or 1).

pred

A numeric vector of predicted probabilities for the positive class.

cut

A numeric threshold (between 0 and 1) to classify predictions into binary labels.

Examples

obs <- c(1, 0, 1, 1, 0)
pred <- c(0.9, 0.4, 0.8, 0.7, 0.3)
cut <- 0.5
measure_bin(obs, pred, cut)
# Returns: list(conf_mat = , accuracy = 1, ROC = , AUC = 1)