python-2.7 – TypeError：预期序列或类似数组,得到估算器

df = pd.read_csv('reviews.csv',header=0)

FEATURES = ['feature1','feature2']
reviews = df['review']
reviews = reviews.values.flatten()

vectorizer = TfidfVectorizer(min_df=1,decode_error='ignore',ngram_range=(1,3),stop_words='english',max_features=45)

X = vectorizer.fit_transform(reviews)
idf = vectorizer.idf_
features = vectorizer.get_feature_names()
FEATURES += features
inverse =  vectorizer.inverse_transform(X)

for i,row in df.iterrows():
    for f in features:
        df.set_value(i,f,False)
    for inv in inverse[i]:
        df.set_value(i,inv,True)

train_df,test_df = train_test_split(df,test_size = 0.2,random_state=700)

上面的代码工作正常.但是当我将max_features从45更改为更高的值时,我在tran_test_split行上出现错误.

错误是：

Traceback(最近一次调用最后一次)：
文件“analysis.py”,第120行,< module>
train_df,random_state = 700)
在train_test_split中输入文件“/Users/user/Tools/anaconda/lib/python2.7/site-packages/sklearn/cross_validation.py”,第1906行
arrays = indexable(* arrays)
文件“/Users/user/Tools/anaconda/lib/python2.7/site-packages/sklearn/utils/validation.py”,第201行,可转位
check_consistent_length(*结果)
在check_consistent_length中输入文件“/Users/user/Tools/anaconda/lib/python2.7/site-packages/sklearn/utils/validation.py”,第173行
uniques = np.unique(如果X不是None,则数组中X为[_ num_samples(X)])
在_num_samples中输入文件“/Users/user/Tools/anaconda/lib/python2.7/site-packages/sklearn/utils/validation.py”,第112行
‘estimator％s’％x)
TypeError：预期序列或类似数组,得到估计量

当我改变增加max_features大小时,我不确定究竟发生了什么变化.

如果您需要更多数据或者我错过了什么,请告诉我