"INFFC"(formula, data, ...)
"INFFC"(x, consensus = FALSE, p = 0.01, s = 3, k = 5, threshold = 0, classColumn = ncol(x), ...)
p
. The filter stops
after s
iterations with not enough noisy instances removed (according to the proportion p
).filter
, which is a list with seven components:
cleanData
is a data frame containing the filtered dataset.
remIdx
is a vector of integers indicating the indexes for
removed instances (i.e. their row number with respect to the original data frame).
repIdx
is a vector of integers indicating the indexes for
repaired/relabelled instances (i.e. their row number with respect to the original data frame).
repLab
is a factor containing the new labels for repaired instances.
parameters
is a list containing the argument values.
call
contains the original call to the filter.
extraInf
is a character that includes additional interesting
information not covered by previous items.
threshold
value.
The process stops after s
iterations with not enough (according to the proportion p
) noisy
instances removed.
# Next example is not run because it might be time-consuming
## Not run:
# data(iris)
# out <- INFFC(Species~., data = iris)
# summary(out)
# identical(out$cleanData, iris[setdiff(1:nrow(iris),out$remIdx),])
# ## End(Not run)
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