e81a11d Merge pull request #25 from daiyl0320/master
35c3b37 add retry mechanism to ConnectTracker and modify Listen backlog to 128 in rabit_traker.py
c71ed6f try deply doxygen
62e5647 try deply doxygen
732f1c6 try
2fa6e02 ok
0537665 minor
7b59dcb minor
5934950 new doc
f538187 ok
44b6049 new doc
387339b add more
9d4397a chg
2879a48 chg
30e3110 ok
9ff0301 add link translation
6b629c2 k
32e1955 ok
8f4839d fix
93137b2 ok
7eeeb79 reload recommonmark
a8f00cc minor
19b0f01 ok
dd01184 minor
c1cdc19 minor
fcf0f43 try rst
cbc21ae try
62ddfa7 tiny
aefc05c final change
2aee9b4 minor
fe4e7c2 ok
8001983 change to subtitle
5ca33e4 ok
88f7d24 update guide
29d43ab add code
fe8bb3b minor hack for readthedocs
229c71d Merge branch 'master' of ssh://github.com/dmlc/rabit
7424218 ok
d1d45bb Update README.md
1e8813f Update README.md
1ccc990 Update README.md
0323e06 remove readme
679a835 remove theme
7ea5b7c remove numpydoc to napoleon
b73e2be Merge branch 'master' of ssh://github.com/dmlc/rabit
1742283 ok
1838e25 Update python-requirements.txt
bc4e957 ok
fba6fc2 ok
0251101 ok
d50b905 ok
d4f2509 ok
cdf401a ok
fef0ef2 new doc
cef360d ok
c125d2a ok
270a49e add requirments
744f901 get the basic doc
1cb5cad Merge branch 'master' of ssh://github.com/dmlc/rabit
8cc07ba minor
d74f126 Update .travis.yml
52b3dcd Update .travis.yml
099581b Update .travis.yml
1258046 Update .travis.yml
7addac9 Update Makefile
0ea7adf Update .travis.yml
f858856 Update travis_script.sh
d8eac4a Update README.md
3cc49ad lint and travis
ceedf4e fix
fd8920c fix win32
8bbed35 modify
9520b90 Merge pull request #14 from dmlc/hjk41
df14bb1 fix type
f441dc7 replace tab with blankspace
2467942 remove unnecessary include
181ef47 defined long long and ulonglong
1582180 use int32_t to define int and int64_t to define long. in VC long is 32bit
e0b7da0 fix
git-subtree-dir: subtree/rabit
git-subtree-split: e81a11dd7ee3cff87a38a42901315821df018bae
- Pandas DataFrame supports more dtypes than 'int64', 'float64' and 'bool', therefor added a bunch of extra dtypes for the data variable.
- From now on the label variable can be a Pandas DataFrame with the same dtypes as the data variable.
- If label is a Pandas DataFrame will be converted to float.
- If no feature_types is set, the data dtypes will be converted to 'int' or 'float'.
- The feature_names may contain every character except [, ] or <
Changed the name of eval_results to evals_result, so that the naming is the same in training.py and sklearn.py
Made the structure of evals_result the same as in training.py, the names of the keys are different:
In sklearn.py you cannot name your evals_result, but they are automatically called 'validation_0', 'validation_1' etc.
The dict evals_result will output something like: {'validation_0': {'logloss': ['0.674800', '0.657121']}, 'validation_1': {'logloss': ['0.63776', '0.58372']}}
In training.py you can name your multiple evals_result with a watchlist like: watchlist = [(dtest,'eval'), (dtrain,'train')]
The dict evals_result will output something like: {'train': {'logloss': ['0.68495', '0.67691']}, 'eval': {'logloss': ['0.684877', '0.676767']}}
You can access the evals_result using the evals_result() function.
