Question

我有如下输入：

list1 = [['Search','engines','using','machine','learning','pattern','detections'],['machine','learning','helped','Google','automatically','sift','pages']]

list2 = ['Machine','learning','ever','evolving','technology']

我尝试了以下代码：

def jaccard_similarity(list1, list2):
    intersection = len(list(set(list1).intersection(list2)))
    print(list(set(list1).intersection(list2)))
    union = (len(list1) + len(list2)) - intersection
    return float(intersection / union)

jaccard_similarity(input_list,input_list1)

得到以下错误：

TypeError: unhashable type: 'list'

Answer 1

我相信您想要做的是为jaccard_similarity中的每个列表获取list1。如果是这样，请遍历它们。另外，对jaccard_similarity中的行进行了小的更正。

list1=[
    ['Search','engines','using','machine','learning','pattern','detections'], 
    ['machine','learning','helped','Google','automatically','sift','pages']
]
list2 = ['Machine','learning','ever','evolving','technology']

def jaccard_similarity(list1, list2):
    intersection = len(set(list1).intersection(list2)) #no need to call list here
    union = len(list1 + list2) - intersection #you only need to call len once here
    return intersection / union #also no need to cast to float as this will be done for you

for l in list1:
    print(jaccard_similarity(l, list2))

或者理解

similarities = [jaccard_similarity(l, list2) for l in list1]

编辑，这是获取jaccard_similarity顺便说一句的简单得多的方法：

def jaccard_similarity(list1, list2):
    s1, s2 = set(list1), set(list2)
    return len(s1 & s2) / len(s1 | s2)

Answer 2

您可以使用函数来计算两个列表之间的Jaccard索引：

jaccard_similarity(list1[0], list2)

返回：

['learning']
Out[7]: 0.09090909090909091

您还可以使用循环将功能应用于list1中的不同子列表，并获取list1和list2子列表之间的Jaccard索引。

如何计算两个字符串列表之间的jaccard相似距离

2 个答案: