Description Usage Arguments Value See Also
Constant features can lead to errors in some models and obviously provide no information in the training set that can be learned from. With the argument “perc”, there is a possibility to also remove features for which less than “perc” percent of the observations differ from the mode value.
1 2 3 | removeConstantFeatures(obj, perc = 0, dont.rm = character(0L),
na.ignore = FALSE, tol = .Machine$double.eps^0.5,
show.info = getMlrOption("show.info"))
|
obj |
[ |
perc |
[ |
dont.rm |
[ |
na.ignore |
[ |
tol |
[ |
show.info |
[ |
[data.frame
| Task
]. Same type as obj
.
Other eda_and_preprocess: capLargeValues
,
createDummyFeatures
,
dropFeatures
,
mergeSmallFactorLevels
,
normalizeFeatures
,
summarizeColumns
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