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add new Gain and Weight columns.

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documentation updated.
This commit is contained in:
El Potaeto 2014-12-30 12:32:58 +01:00
parent c754fd4ad0
commit c6f76fab56
1 changed files with 6 additions and 6 deletions
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R-package/R/xgb.importance.R
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#' Show importance of features in a model
#'
#' Read a xgboost model in text file format.
#' Can be tree or linear model (text dump of linear model are only supported in dev version of Xgboost for now).
#'
#' Read a xgboost model text dump.
#' Can be tree or linear model (text dump of linear model are only supported in dev version of \code{Xgboost} for now).
#' Return a data.table of the features used in the model with their average gain (and their weight for boosted tree model) in the model.
#' #'
#'
#' @importFrom data.table data.table
#' @importFrom magrittr %>%
#' @importFrom data.table :=
#' @importFrom stringr str_extract
#' @param feature_names names of each feature as a character vector. Can be extracted from a sparse matrix (see example). If model dump already contains feature names, this argument should be \code{NULL}.
#' @param filename_dump the path to the text file storing the model.
#' @param filename_dump the path to the text file storing the model. Model dump must include the gain per feature and per tree (\code{with.stats = T} in function \code{xgb.dump}).
#'
#' @details
#' This is the function to understand the model trained (and through your model, your data).
#'
#' Results are returned for both linear and tree models.
#'
#' \code{data.table} is returned by the function.