((Set Distance) The Jaccard Index measures the similarity between finite sample

Question

((Set Distance) The Jaccard Index measures the similarity between finite sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets: A nB A UB Note that 0 SJ(A, B) S 1. The Jaccard distance, which measures similarity between sample sets, is complementary to the Jaccard index and is obtained by subtracting the Jaccard index from1 d) (A, B) = 1-J(A, B) Write a python program named set distance.py which returns the Jaccard distance of two sets. This program includes two functions named

Explanation / Answer

Here is set_distance.py

output:

0.66666666666

Related Questions

Navigate

• Browse (All)
• Browse #
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.