add predict leaf indices

demo/guide-python/README.md

@@ -6,3 +6,4 @@ XGBoost Python Feature Walkthrough
 * [Predicting using first n trees](predict_first_ntree.py)
 * [Generalized Linear Model](generalized_linear_model.py)
 * [Cross validation](cross_validation.py)
+* [Predicting leaf indices](predict_leaf_indices.py)

demo/guide-python/predict_leaf_indices.py

@@ -0,0 +1,22 @@
+#!/usr/bin/python
+import sys
+import numpy as np
+sys.path.append('../../wrapper')
+import xgboost as xgb
+
+### load data in do training
+dtrain = xgb.DMatrix('../data/agaricus.txt.train')
+dtest = xgb.DMatrix('../data/agaricus.txt.test')
+param = {'max_depth':2, 'eta':1, 'silent':1, 'objective':'binary:logistic' }
+watchlist  = [(dtest,'eval'), (dtrain,'train')]
+num_round = 3
+bst = xgb.train(param, dtrain, num_round, watchlist)
+
+print ('start testing predict the leaf indices')
+### predict using first 2 tree
+leafindex = bst.predict(dtest, ntree_limit=2, pred_leaf = True)
+print leafindex.shape
+print leafindex
+### predict all trees
+leafindex = bst.predict(dtest, pred_leaf = True)
+print leafindex.shape

demo/guide-python/runall.sh

@@ -4,4 +4,5 @@ python custom_objective.py
 python boost_from_prediction.py
 python generalized_linear_model.py
 python cross_validation.py
+python predict_leaf_index.py
 rm -rf *~ *.model *.buffer