library(mlbench)
library(mlr)
library(caret)
data("Glass")
## 75% of the sample size
## set the seed to make your partition reproducible
set.seed(123)
train_ind <- createDataPartition(Glass$Type, p = .75,
list = FALSE,
times = 1)
train <- Glass[train_ind, ]
test <- Glass[-train_ind, ]
autostatr(data = train, data_to_predict = test, target = "Type", type = "classif", title= "Glass")
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