本文整理汇总了Python中tpot.TPOT._decision_tree方法的典型用法代码示例。如果您正苦于以下问题：Python TPOT._decision_tree方法的具体用法？Python TPOT._decision_tree怎么用？Python TPOT._decision_tree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._decision_tree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_decision_tree_3
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _decision_tree [as 别名]
def test_decision_tree_3():
"""Ensure that the TPOT decision tree method outputs the same as the sklearn decision tree when min_weight>0.5"""
tpot_obj = TPOT()
result = tpot_obj._decision_tree(training_testing_data, 0.6)
result = result[result['group'] == 'testing']
dtc = DecisionTreeClassifier(min_weight_fraction_leaf=0.5, random_state=42)
dtc.fit(training_features, training_classes)
assert np.array_equal(result['guess'].values, dtc.predict(testing_features))示例2: test_decision_tree
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _decision_tree [as 别名]
def test_decision_tree():
"""Ensure that the TPOT decision tree method outputs the same as the sklearn decision tree"""
tpot_obj = TPOT()
result = tpot_obj._decision_tree(training_testing_data, 0, 0)
result = result[result['group'] == 'testing']
dtc = DecisionTreeClassifier(max_features='auto', max_depth=None, random_state=42)
dtc.fit(training_features, training_classes)
assert np.array_equal(result['guess'].values, dtc.predict(testing_features))