向量化:不是一个有效的集合

Question

我想对包含onecclasssvm分类器训练语料库的文本文件进行矢量化。为此，我使用了scikit-learn库中的CountVectorizer。下面是我的代码:

def file_to_corpse(file_name, stop_words):
    array_file = []
    with open(file_name) as fd:
        corp = fd.readlines()
    array_file = np.array(corp)
    stwf = stopwords.words('french')
    for w in stop_words:
        stwf.append(w)
    vectorizer = CountVectorizer(decode_error = 'replace', stop_words=stwf, min_df=1)
    X = vectorizer.fit_transform(array_file)
    return X

当我在我的文件(大约206346行)上运行我的函数时，我得到以下错误，我似乎无法理解它:

Traceback (most recent call last):
  File "svm.py", line 93, in <module>
    clf_svm.fit(training_data)
  File "/home/imane/anaconda/lib/python2.7/site-packages/sklearn/svm/classes.py", line 1028, in fit
    super(OneClassSVM, self).fit(X, np.ones(_num_samples(X)), sample_weight=sample_weight,
  File "/home/imane/anaconda/lib/python2.7/site-packages/sklearn/utils/validation.py", line 122, in _num_samples
    " a valid collection." % x)
TypeError: Singleton array array(<536172x13800 sparse matrix of type '<type 'numpy.int64'>'
    with 1952637 stored elements in Compressed Sparse Row format>, dtype=object) cannot be considered a valid collection.

有人能帮我解决这个问题吗?我被卡住了一段时间:)

Answer 1

如果你看源代码，你可以在这里找到它例如，你可以发现它检查这个条件是否为真(x是你的数组)

if len(x.shape) == 0:

如果是，它将引发这个异常

TypeError("Singleton array %r cannot be considered a valid collection." % x)

我建议您尝试找出array_file或此函数的返回值是否具有形状长度> 0