本文整理匯總了Python中sklearn.datasets.base.Bunch.train_cover方法的典型用法代碼示例。如果您正苦於以下問題：Python Bunch.train_cover方法的具體用法？Python Bunch.train_cover怎麽用？Python Bunch.train_cover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.datasets.base.Bunch的用法示例。
在下文中一共展示了Bunch.train_cover方法的1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: vectors
# 需要導入模塊: from sklearn.datasets.base import Bunch [as 別名]
# 或者: from sklearn.datasets.base.Bunch import train_cover [as 別名]
Returns
-------
array : shape = [points.shape[0], coverages.shape[0]]
The feature vectors (coverages) for each data point.
"""
rows = []
cols = []
for n in range(points.shape[0]):
i = np.searchsorted(xx, points[n, 0])
j = np.searchsorted(yy, points[n, 1])
rows.append(-j)
cols.append(i)
return coverages[:, rows, cols].T
# Get feature vectors (=coverages)
bv.train_cover = get_coverages(bv.train, coverage, xx, yy)
bv.test_cover = get_coverages(bv.test, coverage, xx, yy)
mm.train_cover = get_coverages(mm.train, coverage, xx, yy)
mm.test_cover = get_coverages(mm.test, coverage, xx, yy)
# background points (grid coordinates) for evaluation
np.random.seed(13)
background_points = np.c_[np.random.randint(low=0, high=n_rows, size=10000),
np.random.randint(low=0, high=n_cols, size=10000)].T
###############################################################################
# Helper functions
def predict(clf, mean, std):