Python AttributeError: 'list' 对象没有属性 'copy'
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AttributeError: 'list' object has no attribute 'copy'
提问by Amr Ragab
I have the following code snippet
我有以下代码片段
classifier = NaiveBayesClassifier.train(train_data)
#classifier.show_most_informative_features(n=20)
results = classifier.classify(test_data)
and the error shows in the following line
错误显示在以下行中
results = classifier.classify(test_data)
error:
错误：
Traceback (most recent call last):
File "trial_trial.py", line 46, in <module>
results = classifier.classify(test_data)
File "c:\Users\Amr\Anaconda\lib\site-packages\nltk\classify\naivebayes.py", line 88, in classify
return self.prob_classify(featureset).max()
File "c:\Users\Amr\Anaconda\lib\site-packages\nltk\classify\naivebayes.py", line 94, in prob_classify
featureset = featureset.copy()
AttributeError: 'list' object has no attribute 'copy'
I think of extending base class list in python and add copy function but I'm not expert in python and I don't know how to solve this problem.
我想在python中扩展基类列表并添加复制功能，但我不是python专家，我不知道如何解决这个问题。
采纳答案by Martijn Pieters
NLTK classifiers work with feature sets; these are always given as dictionaries with feature names mapping to a value. You are passing in a list instead, so you are not producing features as per the NLTK documentation. The code simply expects a Python dictionary, and Python dictionaries have a .copy()method.
NLTK 分类器使用特征集；这些总是作为字典给出，特征名称映射到一个值。您正在传递一个列表，因此您没有按照 NLTK 文档生成功能。代码只需要一个 Python 字典，而 Python 字典有一个.copy()方法。
See the NLTK tutorial chapter on Learning to Classify Text:
请参阅有关学习对文本进行分类的NLTK 教程章节：
The returned dictionary, known as a feature set, maps from feature names to their values. Feature names are case-sensitive strings that typically provide a short human-readable description of the feature, as in the example
'last_letter'. Feature values are values with simple types, such as booleans, numbers, and strings.
返回的字典，称为特征集，从特征名称映射到它们的值。功能名称是区分大小写的字符串，通常提供简短的人类可读的功能描述，如示例中所示
'last_letter'。特征值是具有简单类型的值，例如布尔值、数字和字符串。
Also see the Featuresetssection of the NLTK Classify API documentation:
另请参阅NLTK Classify API 文档的Featuresets部分：
The features describing a token are encoded using a “featureset”, which is a dictionary that maps from “feature names” to “feature values”. Feature names are unique strings that indicate what aspect of the token is encoded by the feature.
描述令牌的特征使用“特征集”进行编码，特征集是从“特征名称”映射到“特征值”的字典。功能名称是唯一的字符串，表示该功能对令牌的哪个方面进行编码。
You haven't shared what kind of objects the train_datalist contains; if those are feature setdictionaries, you want to use classify_many()instead:
您还没有分享train_data列表包含的对象类型；如果这些是功能集词典，您想classify_many()改用：
results = classifier.classify_many(test_data)
That method doestake a list, but each element must still be a valid feature set.
该方法确实需要一个列表，但每个元素仍然必须是一个有效的功能集。
回答by Shemogumbe
The list.copy method does not work both in python 2.x and python 3.x, I wonder why it is still in the documentation. To achieve the results of copying a list, user the list keyword:
list.copy 方法在 python 2.x 和 python 3.x 中都不起作用，我想知道为什么它仍在文档中。要实现复制列表的结果，请使用 list 关键字：
fruits = ['banana', 'cucumber', 'apple', 'water mellon']
my_fruits = list(fruits)
Optionally, you can copy a list by slicing it:
或者，您可以通过切片来复制列表：
my_fruits_copy = fruits[:]
回答by Polipizio
Why do you want do that? if you want set a list equal to another you can do that:
你为什么要这样做？如果你想设置一个列表等于另一个你可以这样做：
a = ['a', 'b', 'c']
b = a
else if you want insert a list inside a secondone you can use append():
否则，如果你想在第二个中插入一个列表，你可以使用 append()：
a = ['a','b','c']
b = ['d','e','f']
for i in len(a):
b.append(i-1)
