在scikit learn GradientBoostingClassifier中设置序列错误的数组元素

问题在于 CountVectorizer :

import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer

d = {'f1': [1, 2], 'f2': ['foo goo', 'goo zoo'], 'target':[0, 1]}
df = pd.DataFrame(data=d)
df['f2'] = CountVectorizer().fit_transform(df['f2'])

df.values 是:

array([[1,
        <2x3 sparse matrix of type '<class 'numpy.int64'>'
    with 4 stored elements in Compressed Sparse Row format>,
        0],
       [2,
        <2x3 sparse matrix of type '<class 'numpy.int64'>'
    with 4 stored elements in Compressed Sparse Row format>,
        1]], dtype=object)

todense()

dense_count = CountVectorizer().fit_transform(df['f2']).todense()

哪里 dense_count 是这样的:

matrix([[1, 1, 0],
        [0, 1, 1]], dtype=int64)