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comment the redundant run_lasso in fit_itr, as it was overwritting lasso in caret algorithms #45

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comment the redundant run_lasso in fit_itr, as it was overwritting lasso in caret algorithms #45

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60 changes: 30 additions & 30 deletions R/main.r
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Original file line number Diff line number Diff line change
Expand Up @@ -307,21 +307,21 @@ fit_itr <- function(
models[["causal_forest"]] <- est$train
}

if("lasso" %in% algorithms){
# run lasso
est <- run_lasso(
dat_train = training_data_elements,
dat_test = testing_data_elements,
dat_total = total_data_elements,
params = params,
indcv = 1,
iter = 1,
budget = budget
)
# store the results
fit_ml[["lasso"]] <- est$test
models[["lasso"]] <- est$train
}
# if("lasso" %in% algorithms){
# # run lasso
# est <- run_lasso(
# dat_train = training_data_elements,
# dat_test = testing_data_elements,
# dat_total = total_data_elements,
# params = params,
# indcv = 1,
# iter = 1,
# budget = budget
# )
# # store the results
# fit_ml[["lasso"]] <- est$test
# models[["lasso"]] <- est$train
# }

if("SuperLearner" %in% algorithms){
# run SuperLearner
Expand Down Expand Up @@ -586,21 +586,21 @@ fit_itr <- function(
models[["causal_forest"]][[j]] <- est$train
}

if("lasso" %in% algorithms){
# run lasso
est <- run_lasso(
dat_train = training_data_elements,
dat_test = testing_data_elements,
dat_total = total_data_elements,
params = params,
indcv = indcv,
iter = j,
budget = budget
)
# store the results
fit_ml[["lasso"]][[j]] <- est$test
models[["lasso"]][[j]] <- est$train
}
# if("lasso" %in% algorithms){
# # run lasso
# est <- run_lasso(
# dat_train = training_data_elements,
# dat_test = testing_data_elements,
# dat_total = total_data_elements,
# params = params,
# indcv = indcv,
# iter = j,
# budget = budget
# )
# # store the results
# fit_ml[["lasso"]][[j]] <- est$test
# models[["lasso"]][[j]] <- est$train
# }

if("SuperLearner" %in% algorithms){
# run SuperLearner
Expand Down