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Create a list of num.boots samples of the original dataset.
num.boots
bootstrap(object, num.boots = 100, seed = 0, imputation = FALSE, k.impute = 10)# S4 method for BNDataset bootstrap(object, num.boots = 100, seed = 0, imputation = FALSE, k.impute = 10)
# S4 method for BNDataset bootstrap(object, num.boots = 100, seed = 0, imputation = FALSE, k.impute = 10)
the BNDataset object.
BNDataset
number of sampled datasets for bootstrap.
random seed.
TRUE if imputation has to be performed. Default is FALSE.
TRUE
FALSE
number of neighbours to be used; for discrete variables we use mode, for continuous variables the median value is instead taken (useful only if imputation == TRUE).
# NOT RUN { dataset <- BNDataset("file.data", "file.header") dataset <- bootstrap(dataset, num.boots = 1000) # } # NOT RUN { # }
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