Sensitivity: Sensitivity

In MLmetrics: Machine Learning Evaluation Metrics

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")

Example output

Attaching package: 'MLmetrics'

The following object is masked from 'package:base':

    Recall

[1] 0.8333333
[1] 0.9285714

MLmetrics documentation built on May 2, 2019, 11:28 a.m.