From e750c4d4237e8e05ac35e61ca10000dcf570a548 Mon Sep 17 00:00:00 2001 From: Erik Sverdrup Date: Thu, 13 May 2021 22:45:33 -0700 Subject: [PATCH] Clarify alpha in the survival_forest docstring (#964) --- r-package/grf/R/survival_forest.R | 6 +++--- r-package/grf/man/survival_forest.Rd | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/r-package/grf/R/survival_forest.R b/r-package/grf/R/survival_forest.R index 12fbc210f..6860d301d 100644 --- a/r-package/grf/R/survival_forest.R +++ b/r-package/grf/R/survival_forest.R @@ -5,7 +5,7 @@ #' #' @param X The covariates. #' @param Y The event time (may be negative). -#' @param D The event type (0: censoring, 1: failure). +#' @param D The event type (0: censored, 1: failure). #' @param failure.times A vector of event times to fit the survival curve at. If NULL, then all the observed #' failure times are used. This speeds up forest estimation by constraining the event grid. Observed event #' times are rounded down to the last sorted occurance less than or equal to the specified failure time. @@ -43,8 +43,8 @@ #' tree is skipped and does not contribute to the estimate). Setting this to FALSE may improve performance on #' small/marginally powered data, but requires more trees (note: tuning does not adjust the number of trees). #' Only applies if honesty is enabled. Default is TRUE. -#' @param alpha A tuning parameter that controls the maximum imbalance of a split. Default is 0.05 -#' (meaning the count of failures on each side of a split has to be at least 5 \% of the total observation count in a node) +#' @param alpha A tuning parameter that controls the maximum imbalance of a split. The number of failures in +#' each child has to be at least one or `alpha` times the number of samples in the parent node. Default is 0.05. #' @param compute.oob.predictions Whether OOB predictions on training set should be precomputed. Default is TRUE. #' @param prediction.type The type of estimate of the survival function, choices are "Kaplan-Meier" or "Nelson-Aalen". #' Only relevant if `compute.oob.predictions` is TRUE. Default is "Kaplan-Meier". diff --git a/r-package/grf/man/survival_forest.Rd b/r-package/grf/man/survival_forest.Rd index 76d82059f..4413e7002 100644 --- a/r-package/grf/man/survival_forest.Rd +++ b/r-package/grf/man/survival_forest.Rd @@ -31,7 +31,7 @@ survival_forest( \item{Y}{The event time (may be negative).} -\item{D}{The event type (0: censoring, 1: failure).} +\item{D}{The event type (0: censored, 1: failure).} \item{failure.times}{A vector of event times to fit the survival curve at. If NULL, then all the observed failure times are used. This speeds up forest estimation by constraining the event grid. Observed event @@ -81,8 +81,8 @@ tree is skipped and does not contribute to the estimate). Setting this to FALSE small/marginally powered data, but requires more trees (note: tuning does not adjust the number of trees). Only applies if honesty is enabled. Default is TRUE.} -\item{alpha}{A tuning parameter that controls the maximum imbalance of a split. Default is 0.05 -(meaning the count of failures on each side of a split has to be at least 5 \% of the total observation count in a node)} +\item{alpha}{A tuning parameter that controls the maximum imbalance of a split. The number of failures in +each child has to be at least one or `alpha` times the number of samples in the parent node. Default is 0.05.} \item{prediction.type}{The type of estimate of the survival function, choices are "Kaplan-Meier" or "Nelson-Aalen". Only relevant if `compute.oob.predictions` is TRUE. Default is "Kaplan-Meier".}