Scikit-Learn GridSearchCV由于隐秘的TypeError而无法与Silhouette_score拟

Question

以下代码在： TypeError: __call__() takes at least 4 arguments (3 given)。

我已经实例化了群集分类器和适用于聚类的创建评分方法。我提供了一个简单的数据集，用于拟合和一个用于网格搜索的参数字典。我很难看到我有错误的地方，而追溯相当无济于事。

from sklearn.mixture import GaussianMixture
from sklearn.model_selection import GridSearchCV
from sklearn.metrics import silhouette_score, make_scorer
parameters = {'n_components': range(1, 6), 'covariance_type': ['full', 'tied', 'diag', 'spherical']}
silhouette_scorer = make_scorer(silhouette_score)
gm = GaussianMixture()
clusterer = GridSearchCV(gm, parameters, scoring=silhouette_scorer)
clusterer.fit(data)

追溯是隐秘的，据我所知，我遵循了GridSearchCV的Sklearn文档中描述的语法和工作流程。我可能在这里做错什么会导致此错误？

这是数据的内容：

     Dimension 1  Dimension 2
0     -0.837489    -1.076500
1      1.746697     0.193893
2     -0.141929    -2.772168
3     -2.809583    -3.645926
4     -2.070939    -2.485348
..           ...          ...
401    -0.477716    -0.347241
402     0.742407     0.005890
403    -2.152810     5.385891
404    -0.074108    -1.691082
405     0.555363    -0.002872
416    -1.597249    -0.804744

这是追溯的最后几行：

/usr/local/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc in __call__(self)
    129 
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
    132 
    133     def __len__(self):
/usr/local/lib/python2.7/site-packages/sklearn/model_selection/_validation.pyc in _fit_and_score(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters, return_n_test_samples, return_times, error_score)
    258     else:
    259         fit_time = time.time() - start_time
--> 260         test_score = _score(estimator, X_test, y_test, scorer)
    261         score_time = time.time() - start_time - fit_time
    262         if return_train_score:
/usr/local/lib/python2.7/site-packages/sklearn/model_selection/_validation.pyc in _score(estimator, X_test, y_test, scorer)
    284     """Compute the score of an estimator on a given test set."""
    285     if y_test is None:
--> 286         score = scorer(estimator, X_test)
    287     else:
    288         score = scorer(estimator, X_test, y_test)
TypeError: __call__() takes at least 4 arguments (3 given)

Answer 1

好吧，问题是，您将错误的函数用作make_scorer的参数。make_scorer的文档说：

score_func - 带签名score_func（y_true，y_pred，** kwargs）

的得分功能（或损失功能）

您正在将silhouette_score传递给具有签名的(X, labels, metric='euclidean' ...)，显然与make_scorer的要求不符，因此是错误的。

尝试将其更改为其他指标以解决错误。