本文整理汇总了Python中tpot.TPOT._extra_trees方法的典型用法代码示例。如果您正苦于以下问题：Python TPOT._extra_trees方法的具体用法？Python TPOT._extra_trees怎么用？Python TPOT._extra_trees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._extra_trees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_extra_trees_3
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _extra_trees [as 别名]
def test_extra_trees_3():
"""Ensure that the TPOT ExtraTreesClassifier outputs the same as the sklearn version when min_weight > 0.5"""
tpot_obj = TPOT()
result = tpot_obj._extra_trees(training_testing_data, 0, 1., 0.6)
result = result[result['group'] == 'testing']
etc = ExtraTreesClassifier(n_estimators=500, random_state=42, max_features=1., min_weight_fraction_leaf=0.5, criterion='gini')
etc.fit(training_features, training_classes)
assert np.array_equal(result['guess'].values, etc.predict(testing_features))示例2: test_extra_trees_3
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _extra_trees [as 别名]
def test_extra_trees_3():
"""Ensure that the TPOT ExtraTreesClassifier outputs the same as the sklearn version when max_features > the number of features"""
tpot_obj = TPOT()
training_features = training_testing_data.loc[training_testing_data['group'] == 'training'].drop(tpot_obj.non_feature_columns, axis=1)
num_features = len(training_features.columns)
result = tpot_obj._extra_trees(training_testing_data, 0, num_features + 1)
result = result[result['group'] == 'testing']
etc = ExtraTreesClassifier(n_estimators=500, random_state=42, max_features=num_features, criterion='gini')
etc.fit(training_features, training_classes)
assert np.array_equal(result['guess'].values, etc.predict(testing_features))