PriceIndices (version 0.0.7)

load_model: Loading the machine learning model from the disk

Description

This function loads a list of machine learning model elements from the disk, i.e. the needed 8 files are read.

Usage

load_model(dir = "ML_model")

Value

This function loads a list of ML model elements from the disk, i.e. the needed 8 files are read from the directory selected by dir. After loading the model it can be used for product classification by using data_classifying function.

Arguments

dir

The name of the directory from which the machine learning model is to be loaded. The directory must be in the working directory.

Examples

#Setting a temporal directory as a working directory
if (FALSE) wd<-tempdir()
if (FALSE) setwd(wd)
#Building the model
if (FALSE) my.grid=list(eta=c(0.01,0.02,0.05),subsample=c(0.5))
if (FALSE) data_train<-dplyr::filter(dataCOICOP,dataCOICOP$time<=as.Date("2020-08-01"))
if (FALSE) data_test<-dplyr::filter(dataCOICOP,dataCOICOP$time>as.Date("2020-08-01"))
if (FALSE) ML<-model_classification(data_train,data_test,grid=my.grid,
indicators=c("prodID","unit","description"),key_words=c("milk"),rounds=50)
#Saving the model
if (FALSE) save_model(ML, dir="My_model")
#Loading the model
if (FALSE) ML_fromPC<-load_model("My_model")
#COICOP predicting
if (FALSE) data_classifying(ML_fromPC, data_test)