feature.fit: Analyze if the missingess of 'target' can be predicted from...
In Stat-Cook/Data.Quality.Reports:
feature.fit R Documentation
Analyze if the missingess of 'target' can be predicted from 'feature'.
'Feature' can be a numeric or categorical vector, and the model is LDA with
a binary decision tree as back up (rpart).
Description
Analyze if the missingess of 'target' can be predicted from 'feature'.
'Feature' can be a numeric or categorical vector, and the model is LDA with
a binary decision tree as back up (rpart).
Usage
feature.fit(target, feature)
Arguments
target
A vector with some values missing
feature
A vector we wish to predict missingess from.
Stat-Cook/Data.Quality.Reports documentation built on May 4, 2022, 2:21 p.m.
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| feature.fit | R Documentation |
Analyze if the missingess of 'target' can be predicted from 'feature'. 'Feature' can be a numeric or categorical vector, and the model is LDA with a binary decision tree as back up (rpart).
Description
Analyze if the missingess of 'target' can be predicted from 'feature'. 'Feature' can be a numeric or categorical vector, and the model is LDA with a binary decision tree as back up (rpart).
Usage
feature.fit(target, feature)
Arguments
target |
A vector with some values missing |
feature |
A vector we wish to predict missingess from. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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