From 6c6d00261cf021206a90c26f4913fa79a7f9d126 Mon Sep 17 00:00:00 2001
From: tqchen <tianqi.tchen@gmail.com>
Date: Thu, 4 Sep 2014 09:18:52 -0700
Subject: [PATCH] small fix to the doc

---
 demo/guide-python/runall.sh |  3 ++-
 wrapper/xgboost.py          | 32 ++++++++++++++++++++------------
 2 files changed, 22 insertions(+), 13 deletions(-)

diff --git a/demo/guide-python/runall.sh b/demo/guide-python/runall.sh
index 4386cf262..ce71f96f2 100755
--- a/demo/guide-python/runall.sh
+++ b/demo/guide-python/runall.sh
@@ -2,4 +2,5 @@
 python basic_walkthrough.py
 python custom_objective.py
 python boost_from_prediction.py
-rm *~ *.model *.buffer 
\ No newline at end of file
+python cross_validation.py
+rm -rf *~ *.model *.buffer 
\ No newline at end of file
diff --git a/wrapper/xgboost.py b/wrapper/xgboost.py
index 34d61bede..643624f35 100644
--- a/wrapper/xgboost.py
+++ b/wrapper/xgboost.py
@@ -296,6 +296,7 @@ class Booster:
                 evals: list of tuple (DMatrix, string)
                        lists of items to be evaluated
                 it: int
+                    current iteration
                 feval: function
                        custom evaluation function
             Returns:
@@ -326,7 +327,8 @@ class Booster:
                 output_margin: bool
                                whether output raw margin value that is untransformed
 
-                ntree_limit: limit number of trees in prediction, default to 0, 0 means using all the trees
+                ntree_limit: int
+                             limit number of trees in prediction, default to 0, 0 means using all the trees
             Returns:
                 numpy array of prediction
         """
@@ -406,14 +408,15 @@ def train(params, dtrain, num_boost_round = 10, evals = [], obj=None, feval=None
                     params of booster
             dtrain: DMatrix
                     data to be trained
-            num_boost_round: int
+            num_boost_round: int 
                              num of round to be boosted
-            evals: list
-                   list of items to be evaluated
+            watchlist: list of pairs (DMatrix, string) 
+                       list of items to be evaluated during training, this allows user to watch performance on validation set
             obj:  function
                    cutomized objective function
             feval: function
                    cutomized evaluation function
+        Returns: Booster model trained
     """
     bst = Booster(params, [dtrain]+[ d[0] for d in evals ] )
     for i in range(num_boost_round):
@@ -487,15 +490,20 @@ def cv(params, dtrain, num_boost_round = 10, nfold=3, metrics=[], \
             num_boost_round: int
                              num of round to be boosted
             nfold: int
-                   folds to do cv
-            evals: list or
-                   list of items to be evaluated
-            obj: custom objective function
-            feval: custom evaluation function
-            fpreproc: preprocessing function that takes dtrain, dtest,
+                   number of folds to do cv
+            metrics: list of strings
+                     evaluation metrics to be watched in cv
+            obj: function 
+                 custom objective function
+            feval: function
+                   custom evaluation function
+            fpreproc: function
+                      preprocessing function that takes dtrain, dtest,
                       param and return transformed version of dtrain, dtest, param
-            show_stdv: whether display standard deviation
-            seed: seed used to generate the folds
+            show_stdv: bool
+                       whether display standard deviation
+            seed: int 
+                  seed used to generate the folds, this is passed to numpy.random.seed
 
         Returns: list(string) of evaluation history
     """