importance.ranger

importance

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

<p>Extract variable importance of ranger object.</p>

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

importance.ranger: ranger variable importance

Description

Usage

Arguments

Value

See Also