Description Usage Arguments Value Methods (by class)
bin
bins a continous variable by maximizing the infomation value.
1 2 3 4 5 6 7 8 9 |
target |
the response variable |
predictor |
the continous variable to bin |
nbin |
numbers of binning |
early_stop_threshold |
iv increasing value less than the threshold will
cause the binning process stopped. If not NA, |
min.node.pct |
the smallest sample proportion of the bins |
p |
p value used for fisher test rejection |
single.values |
some values will be split as a level |
df |
a data frame |
y |
name of target variable |
x |
name of predictor |
a bin
object
cuts
the cut points
IV
the information value
WOE
the weight of evidence tagble
default
: bin.default
data.frame
: bin.data.frame
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