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refactoring of importance function

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El Potaeto
2015-01-07 18:18:52 +01:00
parent d532f04394
commit 3d0bbae2c2
4 changed files with 23 additions and 23 deletions
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R-package/man/xgb.importance.Rd
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@@ -27,7 +27,8 @@ Results are returned for both linear and tree models.
There are 3 columns :
\itemize{
\item \code{Features} name of the features as provided in \code{feature_names} or already present in the model dump.
\item \code{Gain} contribution of each feature to the model. For boosted tree model, each gain of each feature of each tree is taken into account, then average per feature to give a vision of the entire model. Highest percentage means most important feature regarding the \code{label} used for the training.
\item \code{Gain} contribution of each feature to the model. For boosted tree model, each gain of each feature of each tree is taken into account, then average per feature to give a vision of the entire model. Highest percentage means most important feature regarding the \code{label} used for the training ;
\item \code{Cover} metric of the number of observation related to this feature (only available for tree models) ;
\item \code{Weight} percentage representing the relative number of times a feature have been taken into trees. \code{Gain} should be prefered to search the most important feature. For boosted linear model, this column has no meaning.
}
}