import xgboost as xgb

dtrain = xgb.DMatrix('./demo/data/agaricus.txt.train')
dtest = xgb.DMatrix('./demo/data/agaricus.txt.test')
param = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
num_round = 3
watchlist = [(dtest, 'eval'), (dtrain, 'train')]

bst = xgb.train(param, dtrain, num_round, watchlist)

[0]    eval-error:0.042831    train-error:0.046522
[1]    eval-error:0.021726    train-error:0.022263
[2]    eval-error:0.006207    train-error:0.007063

print('Start testing predict the leaf indices')

Start testing predict the leaf indices

leafindex = bst.predict(dtest, ntree_limit = 2, pred_leaf = True)

print(leafindex.shape)

(1611, 2)

print(leafindex)

[[4 3]
 [3 3]
 [4 3]
 ...
 [3 3]
 [5 4]
 [3 3]]

print('Predict all trees')

Predict all trees

leafindex = bst.predict(dtest, pred_leaf = True)

print(leafindex.shape)

(1611, 3)

print(leafindex)

[[4 3 5]
 [3 3 5]
 [4 3 5]
 ...
 [3 3 3]
 [5 4 5]
 [3 3 3]]