accuracy: Accuracy measures

In mpae: Metodos Predictivos de Aprendizaje Estadistico (Statistical Learning Predictive Methods)

Accuracy measures

Description

Computes accuracy measurements.

Usage

accuracy(pred, obs, na.rm = FALSE, tol = sqrt(.Machine$double.eps))

Arguments

pred	a numeric vector with the predicted values.
obs	a numeric vector with the observed values.
na.rm	a logical indicating whether NA values should be stripped before the computation proceeds.
tol	divide underflow tolerance.

Value

Returns a named vector with the following components:

• me mean error

• rmse root mean squared error

• mae mean absolute error

• mpe mean percent error

• mape mean absolute percent error

• r.squared pseudo R-squared

See Also

pred.plot()

Examples

set.seed(1)
nobs <- nrow(bodyfat)
itrain <- sample(nobs, 0.8 * nobs)
train <- bodyfat[itrain, ]
test <- bodyfat[-itrain, ]
fit <- lm(bodyfat ~ abdomen + wrist, data = train)
pred <- predict(fit, newdata = test)
obs <- test$bodyfat
pred.plot(pred, obs)
accuracy(pred, obs)

mpae documentation built on May 29, 2024, 5:25 a.m.