Merge branch 'master' of https://github.com/tqchen/xgboost

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

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)

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
 

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
 

README.md

@@ -30,7 +30,7 @@ Features
 
 Build
 =====
-* Simply type make
+* Run ```bash build.sh``` (you can also type make)
 * If your compiler does not come with OpenMP support, it will fire an warning telling you that the code will compile into single thread mode, and you will get single thread xgboost
 * You may get a error: -lgomp is not found
   - You can type ```make no_omp=1```, this will get you single thread xgboost

build.sh

@@ -0,0 +1,15 @@
+#!/bin/bash
+# this is a simple script to make xgboost in MAC nad Linux
+# basically, it first try to make with OpenMP, if fails, disable OpenMP and make again
+# This will automatically make xgboost for MAC users who do not have openmp support
+# In most cases, type make will give what you want
+if make; then
+    echo "Successfully build multi-thread xgboost"
+else
+    echo "-----------------------------"
+    echo "Building multi-thread xgboost failed"
+    echo "Start to build single-thread xgboost"
+    make clean
+    make no_omp=1
+    echo "Successfully build single-thread xgboost"
+fi