本文整理汇总了Python中tpot.TPOT.score方法的典型用法代码示例。如果您正苦于以下问题：Python TPOT.score方法的具体用法？Python TPOT.score怎么用？Python TPOT.score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.score方法的6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_score
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import score [as 别名]
def test_score():
"""Ensure that the TPOT score function raises a ValueError when no optimized pipeline exists"""
tpot_obj = TPOT()
try:
tpot_obj.score(testing_features, testing_classes)
assert False # Should be unreachable
except ValueError:
pass示例2: test_score_2
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import score [as 别名]
def test_score_2():
"""Ensure that the TPOT score function outputs a known score for a fixed pipeline"""
tpot_obj = TPOT()
tpot_obj._training_classes = training_classes
tpot_obj._training_features = training_features
tpot_obj.pbar = tqdm(total=1, disable=True)
known_score = 0.981993770448 # Assumes use of the TPOT balanced_accuracy function
# Reify pipeline with known score
tpot_obj._optimized_pipeline = creator.Individual.\
from_string('_logistic_regression(input_df, 1.0, 0, True)', tpot_obj._pset)
# Get score from TPOT
score = tpot_obj.score(testing_features, testing_classes)
# http://stackoverflow.com/questions/5595425/
def isclose(a, b, rel_tol=1e-09, abs_tol=0.0):
return abs(a-b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol)
assert isclose(known_score, score)示例3: test_score_2
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import score [as 别名]
def test_score_2():
"""Assert that the TPOT score function outputs a known score for a fixed pipeline"""
tpot_obj = TPOT()
tpot_obj.pbar = tqdm(total=1, disable=True)
known_score = 0.986318199045 # Assumes use of the TPOT balanced_accuracy function
# Reify pipeline with known score
tpot_obj._optimized_pipeline = creator.Individual.\
from_string('RandomForestClassifier(input_matrix)', tpot_obj._pset)
tpot_obj._fitted_pipeline = tpot_obj._toolbox.compile(expr=tpot_obj._optimized_pipeline)
tpot_obj._fitted_pipeline.fit(training_features, training_classes)
# Get score from TPOT
score = tpot_obj.score(testing_features, testing_classes)
# http://stackoverflow.com/questions/5595425/
def isclose(a, b, rel_tol=1e-09, abs_tol=0.0):
return abs(a - b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol)
assert isclose(known_score, score)示例4: load_iris
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import score [as 别名]
from tpot import TPOT
from sklearn.datasets import load_iris
from sklearn.cross_validation import train_test_split
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target,
train_size=0.75, test_size=0.25)
tpot = TPOT(generations=5,verbosity=2)
tpot.fit(X_train, y_train)
print(tpot.score(X_test, y_test))
tpot.export('tpot_iris_pipeline.py')
示例5: TPOT
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import score [as 别名]
import ch9util
from tpot import TPOT
X_train, X_test, y_train, y_test = ch9util.rain_split()
tpot = TPOT(generations=7, population_size=110, verbosity=2)
tpot.fit(X_train, y_train)
print(tpot.score(X_train, y_train, X_test, y_test))
示例6: train_test_split
# 需要导入模块: from tpot import TPOT [as 别名]
# 或者: from tpot.TPOT import score [as 别名]
train = train.drop(drop_list,axis=1)
train = train[0:3000000:300]
train.info(memory_usage='deep')
X = train.drop("hotel_cluster",axis=1).values
y = train.loc[: , "hotel_cluster"].values
del train
import gc
gc.collect()
X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.75,test_size=0.25)
print("got here!")
my_tpot = TPOT(generations=20,verbosity=2,population_size=5) # seems to have a problem with pop <5
# gen 1-> really means two generations!
start = time.clock()
print(start)
my_tpot.fit(X_train, y_train)
my_tpot.export('tpot_expedia_pipeline.py')
end = time.clock()
duration = end - start
score = my_tpot.score(X_test, y_test)
print(duration,score)