x_tu = data_cls_tu.iloc[:,1:].values
y_tu = data_cls_tu.iloc[:,0].values
classifier = DecisionTreeClassifier()
parameters = [{"max_depth": [3,None],
"min_samples_leaf": np.random.randint(1,9),
"criterion": ["gini","entropy"]}]
randomcv = RandomizedSearchCV(estimator=classifier, param_distributions=parameters,
scoring='accuracy', cv=10, n_jobs=-1,
random_state=0)
randomcv.fit(x_tu, y_tu)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-fa8376cb54b8> in <module>()
11 scoring='accuracy', cv=10, n_jobs=-1,
12 random_state=0)
---> 13 randomcv.fit(x_tu, y_tu)
~\Anaconda3\lib\site-packages\sklearn\model_selection\_search.py in fit(self, X, y, groups, **fit_params)
616 n_splits = cv.get_n_splits(X, y, groups)
617 # Regenerate parameter iterable for each fit
--> 618 candidate_params = list(self._get_param_iterator())
619 n_candidates = len(candidate_params)
620 if self.verbose > 0:
~\Anaconda3\lib\site-packages\sklearn\model_selection\_search.py in __iter__(self)
236 # in this case we want to sample without replacement
237 all_lists = np.all([not hasattr(v, "rvs")
--> 238 for v in self.param_distributions.values()])
239 rnd = check_random_state(self.random_state)
240
AttributeError: 'list' object has no attribute 'values'
嗨,我在RandomSearchCV的fit方法上总是遇到错误。
当我在GridSearchCV上使用它们时,它可以工作,但是GridSearchCV需要5个小时才能完成。
x_tu,y_tu都是numpy.ndarray类型。
答案 0 :(得分:4)
param_distributions
必须是dict
对象(documentation),但是您正在传递包含单个dict
的列表。卸下外部方括号,然后应该可以正常工作。
应该是这样的:
parameters = {"max_depth": [3,None],
"min_samples_leaf": [np.random.randint(1,9)],
"criterion": ["gini","entropy"]}