RMSLE: Root Mean Squared Logarithmic Error Loss

In LqNoob/Machine-Learning-Evaluation-Metrics: Machine Learning Evaluation Metrics

Description

Compute the root mean squared logarithmic error regression loss.

Usage

RMSLE(y_pred, y_true)

Arguments

y_pred	Estimated target values vector
y_true	Ground truth (correct) target values vector

Value

Root Mean Squared Logarithmic Error Loss

Examples

data(cars)
reg <- lm(log(dist) ~ log(speed), data = cars)
RMSLE(y_pred = exp(reg$fitted.values), y_true = cars$dist)

LqNoob/Machine-Learning-Evaluation-Metrics documentation built on May 20, 2019, 3:33 p.m.