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remove dependency on bst

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This commit is contained in:
tqchen
2014-08-26 18:06:22 -07:00
parent 46f14b8c27
commit 3c1ed847fb
7 changed files with 25 additions and 20 deletions
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6
wrapper/python-example/demo.py
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@@ -13,7 +13,7 @@ dtrain = xgb.DMatrix('agaricus.txt.train')
dtest = xgb.DMatrix('agaricus.txt.test')
# specify parameters via map, definition are same as c++ version
param = {'bst:max_depth':2, 'bst:eta':1, 'silent':1, 'objective':'binary:logistic' }
param = {'max_depth':2, 'eta':1, 'silent':1, 'objective':'binary:logistic' }
# specify validations set to watch performance
evallist = [(dtest,'eval'), (dtrain,'train')]
@@ -75,7 +75,7 @@ print ('start running example to used cutomized objective function')
# 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 = {'bst:max_depth':2, 'bst:eta':1, 'silent':1 }
param = {'max_depth':2, 'eta':1, 'silent':1 }
# user define objective function, given prediction, return gradient and second order gradient
# this is loglikelihood loss
@@ -107,7 +107,7 @@ bst = xgb.train(param, dtrain, num_round, evallist, logregobj, evalerror)
#
print ('start running example to start from a initial prediction')
# specify parameters via map, definition are same as c++ version
param = {'bst:max_depth':2, 'bst:eta':1, 'silent':1, 'objective':'binary:logistic' }
param = {'max_depth':2, 'eta':1, 'silent':1, 'objective':'binary:logistic' }
# train xgboost for 1 round
bst = xgb.train( param, dtrain, 1, evallist )
# Note: we need the margin value instead of transformed prediction in set_base_margin