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07f04a2e55
* adding jaccard similarity * renaming files. zeebus! what an headache
81 lines
2.3 KiB
Python
81 lines
2.3 KiB
Python
"""
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The Jaccard similarity coefficient is a commonly used indicator of the
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similarity between two sets. Let U be a set and A and B be subsets of U,
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then the Jaccard index/similarity is defined to be the ratio of the number
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of elements of their intersection and the number of elements of their union.
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Inspired from Wikipedia and
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the book Mining of Massive Datasets [MMDS 2nd Edition, Chapter 3]
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https://en.wikipedia.org/wiki/Jaccard_index
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https://mmds.org
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Jaccard similarity is widely used with MinHashing.
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"""
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def jaccard_similariy(setA, setB, alternativeUnion=False):
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"""
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Finds the jaccard similarity between two sets.
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Essentially, its intersection over union.
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The alternative way to calculate this is to take union as sum of the
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number of items in the two sets. This will lead to jaccard similarity
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of a set with itself be 1/2 instead of 1. [MMDS 2nd Edition, Page 77]
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Parameters:
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:setA (set,list,tuple): A non-empty set/list
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:setB (set,list,tuple): A non-empty set/list
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:alternativeUnion (boolean): If True, use sum of number of
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items as union
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Output:
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(float) The jaccard similarity between the two sets.
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Examples:
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>>> setA = {'a', 'b', 'c', 'd', 'e'}
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>>> setB = {'c', 'd', 'e', 'f', 'h', 'i'}
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>>> jaccard_similariy(setA,setB)
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0.375
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>>> jaccard_similariy(setA,setA)
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1.0
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>>> jaccard_similariy(setA,setA,True)
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0.5
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>>> setA = ['a', 'b', 'c', 'd', 'e']
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>>> setB = ('c', 'd', 'e', 'f', 'h', 'i')
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>>> jaccard_similariy(setA,setB)
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0.375
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"""
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if isinstance(setA, set) and isinstance(setB, set):
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intersection = len(setA.intersection(setB))
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if alternativeUnion:
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union = len(setA) + len(setB)
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else:
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union = len(setA.union(setB))
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return intersection / union
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if isinstance(setA, (list, tuple)) and isinstance(setB, (list, tuple)):
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intersection = [element for element in setA if element in setB]
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if alternativeUnion:
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union = len(setA) + len(setB)
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else:
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union = setA + [element for element in setB if element not in setA]
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return len(intersection) / len(union)
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if __name__ == "__main__":
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setA = {"a", "b", "c", "d", "e"}
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setB = {"c", "d", "e", "f", "h", "i"}
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print(jaccard_similariy(setA, setB))
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