6f16f0ef58
* Fix various typos * Add override to functions that are overridden gcc gives warnings about functions that are being overridden by not being marked as oveirridden. This fixes it. * Use bst_float consistently Use bst_float for all the variables that involve weight, leaf value, gradient, hessian, gain, loss_chg, predictions, base_margin, feature values. In some cases, when due to additions and so on the value can take a larger value, double is used. This ensures that type conversions are minimal and reduces loss of precision.
75 lines
1.6 KiB
Python
75 lines
1.6 KiB
Python
# coding: utf-8
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# pylint: disable= invalid-name, unused-import
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"""For compatibility"""
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from __future__ import absolute_import
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import sys
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PY3 = (sys.version_info[0] == 3)
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if PY3:
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# pylint: disable=invalid-name, redefined-builtin
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STRING_TYPES = str,
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def py_str(x):
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"""convert c string back to python string"""
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return x.decode('utf-8')
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else:
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# pylint: disable=invalid-name
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STRING_TYPES = basestring,
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def py_str(x):
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"""convert c string back to python string"""
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return x
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try:
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import cPickle as pickle # noqa
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except ImportError:
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import pickle # noqa
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# pandas
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try:
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from pandas import DataFrame
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PANDAS_INSTALLED = True
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except ImportError:
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class DataFrame(object):
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""" dummy for pandas.DataFrame """
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pass
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PANDAS_INSTALLED = False
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# sklearn
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try:
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from sklearn.base import BaseEstimator
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from sklearn.base import RegressorMixin, ClassifierMixin
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from sklearn.preprocessing import LabelEncoder
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try:
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from sklearn.model_selection import KFold, StratifiedKFold
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except ImportError:
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from sklearn.cross_validation import KFold, StratifiedKFold
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SKLEARN_INSTALLED = True
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XGBModelBase = BaseEstimator
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XGBRegressorBase = RegressorMixin
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XGBClassifierBase = ClassifierMixin
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XGBKFold = KFold
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XGBStratifiedKFold = StratifiedKFold
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XGBLabelEncoder = LabelEncoder
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except ImportError:
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SKLEARN_INSTALLED = False
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# used for compatibility without sklearn
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XGBModelBase = object
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XGBClassifierBase = object
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XGBRegressorBase = object
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XGBKFold = None
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XGBStratifiedKFold = None
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XGBLabelEncoder = None
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