predict.woe

Applies weight of evidence transform of factor variables for binary classification based on a model of class <code>woe</code>.

multivariate

classif

Miscellaneous functions for classification and visualization,
e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes,
an interface to 'svmlight' and stepclass() wrapper variable selection
for supervised classification, partimat() visualization of classification rules
and shardsplot() of cluster results as well as kmodes() clustering for categorical data,
corclust() variable clustering, variable extraction from different variable clustering models
and weight of evidence preprocessing.

Uwe Ligges

klaR

Classification and Visualization

predict.woe function

<dl> <dt>object</dt>
<dd>Object resulting from a call of <code>woe</code>.</dd> <dt>newdata</dt>
<dd>A matrix or data frame where WOE transform should be applied of the same dimension as the data used for training the <code>woe</code> object.</dd> <dt>replace</dt>
<dd>Logical flag specifying whether the original factor variables should be kept in the output.</dd> <dt>...</dt>
<dd>Currently not used.</dd>
 
</dl>

Arguments

Author

Weights of evidence — predict.woe

<dl>

 <dt>object</dt>
<dd>Object resulting from a call of <code>woe</code>.</dd>

 <dt>newdata</dt>
<dd>A matrix or data frame where WOE transform should be applied of the same dimension as the data used for training the <code>woe</code> object.</dd>

 <dt>replace</dt>
<dd>Logical flag specifying whether the original factor variables should be kept in the output.</dd>

 <dt>...</dt>
<dd>Currently not used.</dd>
 
</dl>

predict.woe: Weights of evidence

Description

Usage

Value

Arguments

Author

References

See Also

Examples