将自定义包添加到 Azure 机器学习工作室

Question

我需要使用 azure machine learning studio 上的函数 tsCV 来评估预测模型，但我得到了错误

could not find function "tsCV

我正在尝试更新预测包，但未加载任何包。 我跟着这个教程 http://blog.revolutionanalytics.com/2015/10/using-minicran-in-azure-ml.html 和 https://blog.tallan.com/2016/12/27/adding-r-packages-in-azure-ml/ 但我没有得到相同的结果。 未加载任何包。

我需要一个包含 R 代码的包示例，该包可以在 Azure ML 上运行，或者需要更新预测包以使用 tsCV 函数。

Answer 1

我已经安装了最新版本的预测包，下面是我在安装过程中遵循的步骤。

1. 下载最新版本的 CRAN
2. 确保 tsCV 在本地工作
3. 压缩所有依赖项 + 预测包
4. 将所有生成的 zip 压缩在一起并将其上传到 AMLStudio
5. 运行以下代码：

install.packages("src/glue.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/stringi.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/assertthat.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/fansi.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/utf8.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/stringr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/labeling.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/munsell.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/R6.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/RColorBrewer.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/cli.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/crayon.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/pillar.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/xts.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/TTR.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/curl.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/digest.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/gtable.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/lazyeval.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/plyr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/reshape2.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/rlang.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/scales.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/tibble.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/viridisLite.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/withr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/quadprog.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/quantmod.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/colorspace.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/fracdiff.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/ggplot2.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/lmtest.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/magrittr.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/Rcpp.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/timeDate.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/tseries.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/urca.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/uroot.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/zoo.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/RcppArmadillo.zip", lib = ".", repos = NULL, verbose = TRUE)
install.packages("src/forecast.zip", lib = ".", repos = NULL, verbose = TRUE)

library(forecast, lib.loc=".", verbose=TRUE)
far2 <- function(x, h){forecast(Arima(x, order=c(2,0,0)), h=h)}
e <- tsCV(lynx, far2, h=1)

Here is the zip I have generated: