本文整理匯總了Python中sklearn.linear_model.base.LinearModel方法的典型用法代碼示例。如果您正苦於以下問題：Python base.LinearModel方法的具體用法？Python base.LinearModel怎麽用？Python base.LinearModel使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類sklearn.linear_model.base的用法示例。
在下文中一共展示了base.LinearModel方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_linear_model
# 需要導入模塊: from sklearn.linear_model import base [as 別名]
# 或者: from sklearn.linear_model.base import LinearModel [as 別名]
def test_linear_model(model_cls):
n = 365
# TODO: add test for time other time ranges (e.g. < 365 days)
index = pd.date_range("2019-01-01", periods=n)
X = pd.DataFrame({"foo": np.sin(np.linspace(-10 * np.pi, 10 * np.pi, n)) * 10}, index=index)
y = X + 2
model = model_cls()
model.fit(X, y)
model.predict(X)
assert isinstance(model, LinearModel) 示例2: test_linear_model_prec
# 需要導入模塊: from sklearn.linear_model import base [as 別名]
# 或者: from sklearn.linear_model.base import LinearModel [as 別名]
def test_linear_model_prec(model_cls):
n = 365
# TODO: add test for time other time ranges (e.g. < 365 days)
index = pd.date_range("2019-01-01", periods=n)
X = pd.DataFrame({"foo": np.random.random(n)}, index=index)
y = X + 2
model = model_cls()
model.fit(X, y)
model.predict(X)
assert isinstance(model, LinearModel) 示例3: _checkLM
# 需要導入模塊: from sklearn.linear_model import base [as 別名]
# 或者: from sklearn.linear_model.base import LinearModel [as 別名]
def _checkLM(lm):
if isinstance(lm, (LinearModel, LinearRegression, SparseCoefMixin)):
return lm
raise ValueError("LM class " + _class_name(lm) + " is not supported")