设置参数以在 scikit-learn GridSearchCV 中搜索 - 错误

Question

我正在做一个项目来优化我的 gridsearch 模型，我尝试了以下设置

def model_pipeline_improved():
    pipeline = Pipeline([
                ('text_pipeline', Pipeline([
                    ('vect', CountVectorizer(tokenizer = tokenize)),
                    ('tfidf', TfidfTransformer())
                ])),
        ('clf', MultiOutputClassifier(KNeighborsClassifier()))
    ])
    
    return pipeline

model = model_pipeline_improved()

parameters = {
    'features__text_pipeline__vext__ngram_range': ((1, 1), (1, 2)),
    'features__text_pipeline__vect__max_df': (0.75, 1.0),
    'features__text_pipeline__vect__max_features': (None, 5000),
    'features__text_pipeline__tfidf__use_idf': (True, False),
    }

cv = GridSearchCV(model, param_grid=parameters, verbose= 2, n_jobs=-1)
    
cv.fit(X_train, y_train)

但是，当我运行它时，出现以下错误：

ValueError: Invalid parameter features for estimator Pipeline(memory=None,
     steps=[('text_pipeline', Pipeline(memory=None,
     steps=[('vect', CountVectorizer(analyzer='word', binary=False, decode_error='strict',
        dtype=<class 'numpy.int64'>, encoding='utf-8', input='content',
        lowercase=True, max_df=1.0, max_features=None, min_df=1,
        ngram_range=(1, 1...ric_params=None, n_jobs=1, n_neighbors=5, p=2,
           weights='uniform'),
           n_jobs=1))]). Check the list of available parameters with `estimator.get_params().keys()`.

有人可以帮助我了解我哪里出错了吗？