[英]R fabletools accuracy() first argument should be a forecast object or a time series
I'm trying to pull diagnostics for 3 models at once using the accuracy() function from fabletools.我正在尝试使用 fabletools 中的 accuracy() 函数一次提取 3 个模型的诊断。 I get this error:
我收到此错误:
Error in accuracy.default(rec_fore, df) :
First argument should be a forecast object or a time series.
rec_fore is a tbl_ts. rec_fore 是一个 tbl_ts。 From the online documentation, I believe this function should work on this class without needing to be coerced.
从在线文档中,我相信这个函数应该在这个类上工作,而不需要被强制。 Any tips?
有小费吗? Code below..
下面的代码..
# Train
rec_fit <- df_train %>%
model(
nnar_rec = NNETAR(rec, lambda = "auto"),
arima_rec = ARIMA(rec, stepwise = FALSE, approx = FALSE),
prophet_rec = prophet(rec ~ season(type = "multiplicative"))
)
# Forecast
rec_fore <- rec_fit %>%
forecast(h = 29) %>%
hilo(level = c(95)) %>%
unpack_hilo("95%")
# Diagnose
fabletools::accuracy(rec_fore, df)
This error is coming from the forecast::accuracy.default()
method.此错误来自
forecast::accuracy.default()
方法。 To evaluate test-set forecast accuracy you would use the accuracy()
function with a <fable>
object.要评估测试集的预测准确性,您可以使用带有
<fable>
对象的accuracy()
函数。
Something like this should work:像这样的东西应该工作:
rec_fit %>%
forecast(h = 29) %>%
accuracy(df)
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.