本文整理汇总了Python中tpot.TPOT._select_fwe方法的典型用法代码示例。如果您正苦于以下问题：Python TPOT._select_fwe方法的具体用法？Python TPOT._select_fwe怎么用？Python TPOT._select_fwe使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tpot.TPOT的用法示例。
在下文中一共展示了TPOT._select_fwe方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_select_fwe_4
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _select_fwe [as 别名]
def test_select_fwe_4():
"""Ensure that the TPOT select fwe outputs the same result as sklearn fwe when 0.001 < alpha < 0.05"""
tpot_obj = TPOT()
non_feature_columns = ['class', 'group', 'guess']
training_features = training_testing_data.loc[training_testing_data['group'] == 'training'].drop(non_feature_columns, axis=1)
training_class_vals = training_testing_data.loc[training_testing_data['group'] == 'training', 'class'].values
with warnings.catch_warnings():
warnings.simplefilter('ignore', category=UserWarning)
selector = SelectFwe(f_classif, alpha=0.042)
selector.fit(training_features, training_class_vals)
mask = selector.get_support(True)
mask_cols = list(training_features.iloc[:, mask].columns) + non_feature_columns
assert np.array_equal(tpot_obj._select_fwe(training_testing_data, 0.042), training_testing_data[mask_cols])示例2: test_select_fwe
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _select_fwe [as 别名]
def test_select_fwe():
"""Ensure that the TPOT select fwe outputs the input dataframe when no. of training features is 0"""
tpot_obj = TPOT()
assert np.array_equal(tpot_obj._select_fwe(training_testing_data.ix[:, -3:], 0.005), training_testing_data.ix[:, -3:])