load("./experiments/VEST_PT1_25092020.rdata")
n <- length(RESULTS)
IDS <- 1:90
library(vest)
#lfun <- list(M5.train, M5.predict)
lfun <- list(LASSO.train, LASSO.predict)
H <- 2
FINALRESULTS <- vector("list", n)
for (i in IDS) {
#i<-1
cat(i, "\n")
x <- RESULTS[[i]]
SERIES_RESULTS <- vector("list", length(x))
for (j in 1:length(x)) {
#j<-1
y_test <- x[[j]]$data$test[,"target1"]
y_train <- x[[j]]$data$train[,"target1"]
freq <- x[[j]]$feature_model@keys$freq
#j<-1
tres <- WF_part2_direct2(x = x[[j]],
learning_functions = lfun,
h = H)
yhat_cls <-
run_classical_methods(y_train = y_train,
y_test = y_test,
freq = freq,
h = H)
tres$yhat <- c(tres$yhat, yhat_cls)
SERIES_RESULTS[[j]] <- tres
}
FINALRESULTS[[i]] <- SERIES_RESULTS
SIGNATURE <- paste0("F", IDS[1], "_", IDS[length(IDS)])
save(FINALRESULTS,
file = paste0("experiments/VEST_PT2_DIR_LASSO_",
SIGNATURE, ".rdata"))
}
SIGNATURE <- paste0("F", IDS[1], "_", IDS[length(IDS)])
a <- ""
save(a, file = paste0("FINITO_",SIGNATURE,".rdata"))
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