importance.ranger

importance

Further arguments passed to or from other methods.

Extract variable importance of ranger object.

A fast implementation of Random Forests, particularly suited for high
dimensional data. Ensembles of classification, regression, survival and
probability prediction trees are supported. Data from genome-wide association
studies can be analyzed efficiently. In addition to data frames, datasets of
class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix')
can be directly analyzed.

Marvin Wright

ranger

A Fast Implementation of Random Forests

importance.ranger function

<dl><dt>x</dt>
<dd>ranger object.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Author

ranger variable importance — importance.ranger

<dl>

<dt>x</dt>
<dd>ranger object.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

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importance.ranger: ranger variable importance

Description

Usage

Value

Arguments

Author

See Also