PriceIndices (version 0.2.3)

save_model: Saving the machine learning model on the disk

Description

This function saves a list of machine learning model elements on the disk, i.e. the resulting 8 files are written.

Usage

save_model(model = list(), dir = "ML_model")

Value

This function saves a list of ML model elements on the disk, i.e. the resulting 8 files are written into the new directory specified by dir. The list should be obtained previously using the model_classification function. After saving the model, it can be loaded at any time by using the load_model function.

Arguments

model

A list of 8 elements which identify the previously built machine learning model (the list is obtained via the model_classification function).

dir

The name of the directory where the selected model should be saved. The directory with all necessary files will be created in the working directory.

Examples

#Setting a temporal directory as a working director
if (FALSE) wd<-tempdir()
if (FALSE) setwd(wd)
#Building the model
#Building the model
my.grid=list(eta=c(0.01,0.02,0.05),subsample=c(0.5,0.8))
data_train<-dplyr::filter(dataCOICOP,dataCOICOP$time<=as.Date("2021-10-01"))
data_test<-dplyr::filter(dataCOICOP,dataCOICOP$time==as.Date("2021-11-01"))
ML<-model_classification(data_train,data_test,class="coicop6",grid=my.grid,
indicators=c("description","codeIN", "grammage"),key_words=c("uht"),rounds=60)
#Saving the model
if (FALSE) save_model(ML, dir="My_model")