Unverified Commit 68b7315f authored by Sebastian Fischer's avatar Sebastian Fischer Committed by GitHub
Browse files

[R-package] [docs] fix typo in documentation on init_model (#5379)



* docs: typo in documentation of parameter init_model

* docs: actually fix typo and build docs
Co-authored-by: default avatarJames Lamb <jaylamb20@gmail.com>
parent f12d4651
...@@ -44,7 +44,7 @@ ...@@ -44,7 +44,7 @@
#' } #' }
#' } #' }
#' @param eval_freq evaluation output frequency, only effective when verbose > 0 and \code{valids} has been provided #' @param eval_freq evaluation output frequency, only effective when verbose > 0 and \code{valids} has been provided
#' @param init_model path of model file of \code{lgb.Booster} object, will continue training from this model #' @param init_model path of model file or \code{lgb.Booster} object, will continue training from this model
#' @param nrounds number of training rounds #' @param nrounds number of training rounds
#' @param obj objective function, can be character or custom objective function. Examples include #' @param obj objective function, can be character or custom objective function. Examples include
#' \code{regression}, \code{regression_l1}, \code{huber}, #' \code{regression}, \code{regression_l1}, \code{huber},
......
...@@ -101,7 +101,7 @@ by the values of outcome labels.} ...@@ -101,7 +101,7 @@ by the values of outcome labels.}
(each element must be a vector of test fold's indices). When folds are supplied, (each element must be a vector of test fold's indices). When folds are supplied,
the \code{nfold} and \code{stratified} parameters are ignored.} the \code{nfold} and \code{stratified} parameters are ignored.}
\item{init_model}{path of model file of \code{lgb.Booster} object, will continue training from this model} \item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model}
\item{colnames}{feature names, if not null, will use this to overwrite the names in dataset} \item{colnames}{feature names, if not null, will use this to overwrite the names in dataset}
......
...@@ -80,7 +80,7 @@ printing of evaluation during training} ...@@ -80,7 +80,7 @@ printing of evaluation during training}
\item{eval_freq}{evaluation output frequency, only effective when verbose > 0 and \code{valids} has been provided} \item{eval_freq}{evaluation output frequency, only effective when verbose > 0 and \code{valids} has been provided}
\item{init_model}{path of model file of \code{lgb.Booster} object, will continue training from this model} \item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model}
\item{colnames}{feature names, if not null, will use this to overwrite the names in dataset} \item{colnames}{feature names, if not null, will use this to overwrite the names in dataset}
......
...@@ -52,7 +52,7 @@ set to the iteration number of the best iteration.} ...@@ -52,7 +52,7 @@ set to the iteration number of the best iteration.}
\item{eval_freq}{evaluation output frequency, only effective when verbose > 0 and \code{valids} has been provided} \item{eval_freq}{evaluation output frequency, only effective when verbose > 0 and \code{valids} has been provided}
\item{init_model}{path of model file of \code{lgb.Booster} object, will continue training from this model} \item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model}
\item{nrounds}{number of training rounds} \item{nrounds}{number of training rounds}
......
...@@ -48,7 +48,7 @@ fails to improve for \code{early_stopping_rounds} consecutive boosting rounds. ...@@ -48,7 +48,7 @@ fails to improve for \code{early_stopping_rounds} consecutive boosting rounds.
If training stops early, the returned model will have attribute \code{best_iter} If training stops early, the returned model will have attribute \code{best_iter}
set to the iteration number of the best iteration.} set to the iteration number of the best iteration.}
\item{init_model}{path of model file of \code{lgb.Booster} object, will continue training from this model} \item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model}
\item{callbacks}{List of callback functions that are applied at each iteration.} \item{callbacks}{List of callback functions that are applied at each iteration.}
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment