Sensitivity: Sensitivity

In yanyachen/MLmetrics: Machine Learning Evaluation Metrics

Sensitivity

Description

Compute the sensitivity score.

Usage

Sensitivity(y_true, y_pred, positive = NULL)

Arguments

y_true	Ground truth (correct) 0-1 labels vector
y_pred	Predicted labels vector, as returned by a classifier
positive	An optional character string for the factor level that corresponds to a "positive" result

Value

Sensitivity

Examples

data(cars)
logreg <- glm(formula = vs ~ hp + wt,
              family = binomial(link = "logit"), data = mtcars)
pred <- ifelse(logreg$fitted.values < 0.5, 0, 1)
Sensitivity(y_pred = pred, y_true = mtcars$vs, positive = "0")
Sensitivity(y_pred = pred, y_true = mtcars$vs, positive = "1")

yanyachen/MLmetrics documentation built on April 16, 2024, 7:48 a.m.