From 89b9965cbf97e099aa4be1afcd94f74517f2f679 Mon Sep 17 00:00:00 2001
From: tqchen <tianqi.tchen@gmail.com>
Date: Sat, 6 Sep 2014 22:40:51 -0700
Subject: [PATCH]  change max depth

---
 R-package/demo/boost_from_prediction.R | 2 +-
 R-package/demo/cross_validation.R      | 4 ++--
 R-package/demo/custom_objective.R      | 2 +-
 R-package/demo/predict_first_ntree.R   | 2 +-
 4 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/R-package/demo/boost_from_prediction.R b/R-package/demo/boost_from_prediction.R
index 7372717f8..bbf45f4a0 100644
--- a/R-package/demo/boost_from_prediction.R
+++ b/R-package/demo/boost_from_prediction.R
@@ -11,7 +11,7 @@ watchlist <- list(eval = dtest, train = dtrain)
 #
 print('start running example to start from a initial prediction')
 # train xgboost for 1 round
-param <- list(max_depth=2,eta=1,silent=1,objective='binary:logistic')
+param <- list(max.depth=2,eta=1,silent=1,objective='binary:logistic')
 bst <- xgb.train( param, dtrain, 1, watchlist )
 # Note: we need the margin value instead of transformed prediction in set_base_margin
 # do predict with output_margin=TRUE, will always give you margin values before logistic transformation
diff --git a/R-package/demo/cross_validation.R b/R-package/demo/cross_validation.R
index 7fa1f16b2..c7e7ba537 100644
--- a/R-package/demo/cross_validation.R
+++ b/R-package/demo/cross_validation.R
@@ -6,7 +6,7 @@ dtrain <- xgb.DMatrix(agaricus.train$data, label = agaricus.train$label)
 dtest <- xgb.DMatrix(agaricus.test$data, label = agaricus.test$label)
 
 nround <- 2
-param <- list(max_depth=2,eta=1,silent=1,objective='binary:logistic')
+param <- list(max.depth=2,eta=1,silent=1,objective='binary:logistic')
 
 cat('running cross validation\n')
 # do cross validation, this will print result out as
@@ -40,7 +40,7 @@ evalerror <- function(preds, dtrain) {
   return(list(metric = "error", value = err))
 }
 
-param <- list(max_depth=2,eta=1,silent=1)
+param <- list(max.depth=2,eta=1,silent=1)
 # train with customized objective
 xgb.cv(param, dtrain, nround, nfold = 5,
        obj = logregobj, feval=evalerror)
diff --git a/R-package/demo/custom_objective.R b/R-package/demo/custom_objective.R
index 017961876..9b0d45465 100644
--- a/R-package/demo/custom_objective.R
+++ b/R-package/demo/custom_objective.R
@@ -8,7 +8,7 @@ dtest <- xgb.DMatrix(agaricus.test$data, label = agaricus.test$label)
 # note: for customized objective function, we leave objective as default
 # note: what we are getting is margin value in prediction
 # you must know what you are doing
-param <- list(max_depth=2,eta=1,silent=1)
+param <- list(max.depth=2,eta=1,silent=1)
 watchlist <- list(eval = dtest, train = dtrain)
 num_round <- 2
 
diff --git a/R-package/demo/predict_first_ntree.R b/R-package/demo/predict_first_ntree.R
index f8e45f2d8..964203e9f 100644
--- a/R-package/demo/predict_first_ntree.R
+++ b/R-package/demo/predict_first_ntree.R
@@ -5,7 +5,7 @@ data(agaricus.test, package='xgboost')
 dtrain <- xgb.DMatrix(agaricus.train$data, label = agaricus.train$label)
 dtest <- xgb.DMatrix(agaricus.test$data, label = agaricus.test$label)
 
-param <- list(max_depth=2,eta=1,silent=1,objective='binary:logistic')
+param <- list(max.depth=2,eta=1,silent=1,objective='binary:logistic')
 watchlist <- list(eval = dtest, train = dtrain)
 nround = 2