add more docs

This commit is contained in:
tqchen
2015-04-19 00:55:11 -07:00
parent ee112353cb
commit 5123b07d73
6 changed files with 315 additions and 0 deletions

View File

@@ -7,3 +7,5 @@ XGBoost Python Feature Walkthrough
* [Generalized Linear Model](generalized_linear_model.py)
* [Cross validation](cross_validation.py)
* [Predicting leaf indices](predict_leaf_indices.py)
* [Sklearn Wrapper](sklearn_example.py)
* [External Memory](external_memory.py)

View File

@@ -0,0 +1,25 @@
#!/usr/bin/python
import numpy as np
import scipy.sparse
import xgboost as xgb
### simple example for using external memory version
# this is the only difference, add a # followed by a cache prefix name
# several cache file with the prefix will be generated
# currently only support convert from libsvm file
dtrain = xgb.DMatrix('../data/agaricus.txt.train#dtrain.cache')
dtest = xgb.DMatrix('../data/agaricus.txt.test#dtest.cache')
# specify validations set to watch performance
param = {'max_depth':2, 'eta':1, 'silent':1, 'objective':'binary:logistic' }
# performance notice: set nthread to be the number of your real cpu
# some cpu offer two threads per core, for example, a 4 core cpu with 8 threads, in such case set nthread=4
#param['nthread']=num_real_cpu
watchlist = [(dtest,'eval'), (dtrain,'train')]
num_round = 2
bst = xgb.train(param, dtrain, num_round, watchlist)