gaussian_metrics {cvms}R Documentation

Select metrics for Gaussian evaluation

Description

[Experimental]

Enable/disable metrics for Gaussian evaluation. Can be supplied to the `metrics` argument in many of the cvms functions.

Note: Some functions may have slightly different defaults than the ones supplied here.

Usage

gaussian_metrics(
  all = NULL,
  rmse = NULL,
  mae = NULL,
  nrmse_rng = NULL,
  nrmse_iqr = NULL,
  nrmse_std = NULL,
  nrmse_avg = NULL,
  rae = NULL,
  rse = NULL,
  rrse = NULL,
  rmsle = NULL,
  male = NULL,
  mape = NULL,
  mse = NULL,
  tae = NULL,
  tse = NULL,
  r2m = NULL,
  r2c = NULL,
  aic = NULL,
  aicc = NULL,
  bic = NULL
)

Arguments

all

Enable/disable all arguments at once. (Logical)

Specifying other metrics will overwrite this, why you can use (all = FALSE, rmse = TRUE) to get only the RMSE metric.

rmse

RMSE. (Default: TRUE)

Root Mean Square Error.

mae

MAE. (Default: TRUE)

Mean Absolute Error.

nrmse_rng

NRMSE(RNG). (Default: FALSE)

Normalized Root Mean Square Error (by target range).

nrmse_iqr

NRMSE(IQR). (Default: TRUE)

Normalized Root Mean Square Error (by target interquartile range).

nrmse_std

NRMSE(STD). (Default: FALSE)

Normalized Root Mean Square Error (by target standard deviation).

nrmse_avg

NRMSE(AVG). (Default: FALSE)

Normalized Root Mean Square Error (by target mean).

rae

RAE. (Default: TRUE)

Relative Absolute Error.

rse

RSE. (Default: FALSE)

Relative Squared Error.

rrse

RRSE. (Default: TRUE)

Root Relative Squared Error.

rmsle

RMSLE. (Default: TRUE)

Root Mean Square Log Error.

male

MALE. (Default: FALSE)

Mean Absolute Log Error.

mape

MAPE. (Default: FALSE)

Mean Absolute Percentage Error.

mse

MSE. (Default: FALSE)

Mean Square Error.

tae

TAE. (Default: FALSE)

Total Absolute Error

tse

TSE. (Default: FALSE)

Total Squared Error.

r2m

r2m. (Default: FALSE)

Marginal R-squared.

r2c

r2c. (Default: FALSE)

Conditional R-squared.

aic

AIC. (Default: FALSE)

Akaike Information Criterion.

aicc

AICc. (Default: FALSE)

Corrected Akaike Information Criterion.

bic

BIC. (Default: FALSE)

Bayesian Information Criterion.

Author(s)

Ludvig Renbo Olsen, r-pkgs@ludvigolsen.dk

See Also

Other evaluation functions: binomial_metrics(), confusion_matrix(), evaluate_residuals(), evaluate(), multinomial_metrics()

Examples


# Attach packages
library(cvms)

# Enable only RMSE
gaussian_metrics(all = FALSE, rmse = TRUE)

# Enable all but RMSE
gaussian_metrics(all = TRUE, rmse = FALSE)

# Disable RMSE
gaussian_metrics(rmse = FALSE)


[Package cvms version 1.3.3 Index]