get_var_imp: Variable importance for forecasting model.

In caretForecast: Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms

Variable importance for forecasting model.

Description

Variable importance for forecasting model.

Usage

get_var_imp(object, plot = TRUE)

Arguments

object	A list class of ARml or forecast object derived from ARml
plot	Boolean, if TRUE, variable importance will be ploted.

Value

A list class of "varImp.train". See varImp or a "trellis" plot.

Author(s)

Resul Akay

Examples

train <- window(AirPassengers, end = c(1959, 12))

test <- window(AirPassengers, start = c(1960, 1))

ARml(train, caret_method = "lm", max_lag = 12, trend_method = "none",
 pre_process = "center") -> fit

forecast(fit, h = length(test), level = c(80,95)) -> fc

autoplot(fc)+ autolayer(test)

accuracy(fc, test)

get_var_imp(fc, plot = TRUE)

caretForecast documentation built on Oct. 24, 2022, 9:07 a.m.