You can save and load treatment plans. Note: treatments plans are intended to be used with the version of vtreat
they were constructed with (though we try to make plans forward-compatible). So it is good idea to have procedures to re-build treatment plans.
The easiest way to save vtreat
treatment plans is to use R
's built in
saveRDS
function.
To save in a file:
library("vtreat") dTrainC <- data.frame(x=c('a','a','a','b','b',NA,NA), z=c(1,2,3,4,NA,6,NA), y=c(FALSE,FALSE,TRUE,FALSE,TRUE,TRUE,TRUE)) treatmentsC <- designTreatmentsC(dTrainC, colnames(dTrainC), 'y', TRUE, verbose= FALSE) fileName = paste0(tempfile(c('vtreatPlan')), '.RDS') saveRDS(treatmentsC,fileName) rm(list=c('treatmentsC'))
And then to restore and use.
library("vtreat") treatmentsC <- readRDS(fileName) dTestC <- data.frame(x=c('a','b','c',NA),z=c(10,20,30,NA)) dTestCTreated <- prepare(treatmentsC, dTestC, pruneSig= c()) # clean up unlink(fileName)
Treatment plans can also be stored as binary blobs in databases.
Using ideas from here gives us the following through the DBI
interface.
con <- NULL if (requireNamespace('RSQLite', quietly = TRUE) && requireNamespace('DBI', quietly = TRUE)) { library("RSQLite") con <- dbConnect(drv=SQLite(), dbname=":memory:") # create table dbExecute(con, 'create table if not exists treatments (key varchar(200) primary key, treatment blob)') # wrap data df <- data.frame( key='treatmentsC', treatment = I(list(serialize(treatmentsC, NULL)))) # Clear any previous version dbExecute(con, "delete from treatments where key='treatmentsC'") # insert treatmentplan # depreciated # dbGetPreparedQuery(con, # 'insert into treatments (key, treatment) values (:key, :treatment)', # bind.data=df) dbExecute(con, 'insert into treatments (key, treatment) values (:key, :treatment)', params=df) constr <- paste(capture.output(print(con)),collapse='\n') paste('saved to db: ', constr) } rm(list= c('treatmentsC', 'dTestCTreated'))
And we can read the treatment back in as follows.
if(!is.null(con)) { treatmentsList <- lapply( dbGetQuery(con, "select * from treatments where key='treatmentsC'")$treatment, unserialize) treatmentsC <- treatmentsList[[1]] dbDisconnect(con) dTestCTreated <- prepare(treatmentsC, dTestC, pruneSig= c()) print(dTestCTreated) }
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