Question

我正在使用来自scikit-learn 0.14的GridSearchCV，但总是收到以下警告：

/Library/Frameworks/EPD64.framework/Versions/7.2/lib/python2.7/site-packages/sklearn/grid_search.py:706:DreprecationWarning：忽略GridSearchCV的其他参数！ params参数将在0.15中删除。 DeprecationWarning）

有谁确切知道哪些参数被忽略了？

代码（从文件中读取x和y）：

def balanced_accuracy (ground_truth, predictions):
    f00 = 1. * ((ground_truth == 1) & (predictions == 1)).sum() / (ground_truth == 1).sum()
    f11 = 1. * ((ground_truth == 2) & (predictions == 2)).sum() / (ground_truth == 2).sum()
    return 0.5* (f00 + f11)

bc_score = make_scorer(balanced_accuracy, greater_is_better=True)

C_range = 10. ** np.arange(-3, 3)
gamma_range = 10. ** np.arange(-3, 3)
r_range = np.concatenate((np.array([0]), 10.0 ** np.arange(-1, 3)))
kernel = "poly"
deg = 2
cw = "auto"

param_grid = dict(C=C_range, coef0 = r_range, gamma=gamma_range)
ss = ShuffleSplit(len(y), 10, test_size = 1000, train_size = 1000)

grid = GridSearchCV(svm.SVC(kernel = kernel, max_iter = 1000000, degree = deg, class_weight = cw), param_grid=param_grid, cv=ss, scoring = bc_score)
grid.fit (x, y, sample_weight = sw)

提前致谢！

Answer 1

sample_weight的{{1}}参数已弃用。这在文档中都是明显的，并且通过查看0.14.X release branch of scikit-learn's source。

在这种情况下，在0.14版本中也会忽略sample_weight，因此grid.fit等同于grid.fit(x, y sample_weight=sw)。

作为旁注，根据pep-8写一个好主意。

scikit-learn GridSearchCV弃用警告

1 个答案: