Question

我正在使用以下代码来优化随机森林算法，但这会抛出一个类型错误：'str'对象不可调用。能否请你帮我确定可能的原因？拟合线在scorer.py文件中抛出了这个“score = scorer（estimator，X_test，y_test）”的错误

from sklearn.grid_search import GridSearchCV
from sklearn.metrics import roc_auc_score, make_scorer
clf_scorer = make_scorer('roc_auc')
rfc = RandomForestClassifier(n_estimators=100,oob_score=True)
param_grid = {
    'max_depth':[4,8,12],
}

cv_rfc = GridSearchCV(estimator=rfc, param_grid=param_grid, cv=5, 
scoring=clf_scorer)
cv_rfc.fit(train_data,target)

以下是cross_validation.py提供错误的代码：

def _score(estimator, X_test, y_test, scorer):
    """Compute the score of an estimator on a given test set."""
    if y_test is None:
        score = scorer(estimator, X_test)
    else:
        **score = scorer(estimator, X_test, y_test)**
    if hasattr(score, 'item'):
        try:
            # e.g. unwrap memmapped scalars
            score = score.item()
        except ValueError:
            # non-scalar?
            pass
    if not isinstance(score, numbers.Number):
        raise ValueError("scoring must return a number, got %s (%s) instead."
                         % (str(score), type(score)))
    return score

Answer 1

将第三行更改为：

clf_scorer = make_scorer(roc_auc_score)

第一个参数score_func需要是一个可调用的评分函数。

make_scorer给出错误：'str'对象不可调用make_scorer

1 个答案: