本文整理汇总了Python中tpot.TPOT._random_forest方法的典型用法代码示例。如果您正苦于以下问题：Python TPOT._random_forest方法的具体用法？Python TPOT._random_forest怎么用？Python TPOT._random_forest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._random_forest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_random_forest_2
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _random_forest [as 别名]
def test_random_forest_2():
"""Ensure that the TPOT random forest method outputs the same as the sklearn random forest when min_weight>0.5"""
tpot_obj = TPOT()
result = tpot_obj._random_forest(training_testing_data, 0.6)
result = result[result['group'] == 'testing']
rfc = RandomForestClassifier(n_estimators=500, min_weight_fraction_leaf=0.5, random_state=42, n_jobs=-1)
rfc.fit(training_features, training_classes)
assert np.array_equal(result['guess'].values, rfc.predict(testing_features))示例2: test_random_forest
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import _random_forest [as 别名]
def test_random_forest():
"""Ensure that the TPOT random forest method outputs the same as the sklearn random forest"""
tpot_obj = TPOT()
result = tpot_obj._random_forest(training_testing_data, 100, 0)
result = result[result['group'] == 'testing']
rfc = RandomForestClassifier(n_estimators=100, max_features='auto', random_state=42, n_jobs=-1)
rfc.fit(training_features, training_classes)
assert np.array_equal(result['guess'].values, rfc.predict(testing_features))