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fix a typo and some code format (#1470)

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* fix a typo

* fix a typo and some code format
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闻波 2016-08-19 03:41:18 +08:00 committed by Tianqi Chen
parent d85e287b99
commit 669a387c99
1 changed files with 5 additions and 5 deletions
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10
demo/guide-python/custom_objective.py
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@ -2,9 +2,9 @@
import numpy as np import numpy as np
import xgboost as xgb import xgboost as xgb
### ###
# advanced: cutomsized loss function # advanced: customized loss function
# #
print ('start running example to used cutomized objective function') print ('start running example to used customized objective function')
dtrain = xgb.DMatrix('../data/agaricus.txt.train') dtrain = xgb.DMatrix('../data/agaricus.txt.train')
dtest = xgb.DMatrix('../data/agaricus.txt.test') dtest = xgb.DMatrix('../data/agaricus.txt.test')
@ -12,12 +12,12 @@ dtest = xgb.DMatrix('../data/agaricus.txt.test')
# note: for customized objective function, we leave objective as default # note: for customized objective function, we leave objective as default
# note: what we are getting is margin value in prediction # note: what we are getting is margin value in prediction
# you must know what you are doing # you must know what you are doing
param = {'max_depth':2, 'eta':1, 'silent':1 } param = {'max_depth': 2, 'eta': 1, 'silent': 1}
watchlist = [(dtest,'eval'), (dtrain,'train')] watchlist = [(dtest, 'eval'), (dtrain, 'train')]
num_round = 2 num_round = 2
# user define objective function, given prediction, return gradient and second order gradient # user define objective function, given prediction, return gradient and second order gradient
# this is loglikelihood loss # this is log likelihood loss
def logregobj(preds, dtrain): def logregobj(preds, dtrain):
labels = dtrain.get_label() labels = dtrain.get_label()
preds = 1.0 / (1.0 + np.exp(-preds)) preds = 1.0 / (1.0 + np.exp(-preds))