当前位置: 首页>>代码示例>>Python>>正文


Python TPOT._extra_trees方法代码示例

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))
开发者ID:ANSWER1992,项目名称:tpot,代码行数:13,代码来源:tests.py

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))
开发者ID:0x0all,项目名称:tpot,代码行数:16,代码来源:tests.py


注:本文中的tpot.TPOT._extra_trees方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。