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  2. Multiset - Wikipedia

    en.wikipedia.org/wiki/Multiset

    In mathematics, a multiset (or bag, or mset) is a modification of the concept of a set that, unlike a set, [1] allows for multiple instances for each of its elements.The number of instances given for each element is called the multiplicity of that element in the multiset.

  3. Set (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Set_(abstract_data_type)

    Python has built-in set and frozenset types since 2.4, and since Python 3.0 and 2.7, supports non-empty set literals using a curly-bracket syntax, e.g.: {x, y, z}; empty sets must be created using set(), because Python uses {} to represent the empty dictionary.

  4. List comprehension - Wikipedia

    en.wikipedia.org/wiki/List_comprehension

    Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.

  5. Nested set model - Wikipedia

    en.wikipedia.org/wiki/Nested_set_model

    Nested Sets is a clever solution – maybe too clever. It also fails to support referential integrity. It’s best used when you need to query a tree more frequently than you need to modify the tree. [9] The model doesn't allow for multiple parent categories. For example, an 'Oak' could be a child of 'Tree-Type', but also 'Wood-Type'.

  6. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    The most naïve algorithm would be to cycle through all subsets of n numbers and, for every one of them, check if the subset sums to the right number. The running time is of order (), since there are subsets and, to check each subset, we need to sum at most n elements.

  7. Set cover problem - Wikipedia

    en.wikipedia.org/wiki/Set_cover_problem

    In the set cover optimization problem, the input is a pair (,), and the task is to find a set cover that uses the fewest sets. The decision version of set covering is NP-complete . It is one of Karp's 21 NP-complete problems shown to be NP-complete in 1972.

  8. Disjoint-set data structure - Wikipedia

    en.wikipedia.org/wiki/Disjoint-set_data_structure

    In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that stores a collection of disjoint (non-overlapping) sets. Equivalently, it stores a partition of a set into disjoint subsets .

  9. Bijection - Wikipedia

    en.wikipedia.org/wiki/Bijection

    A bijection from the natural numbers to the integers, which maps 2n to −n and 2n − 1 to n, for n ≥ 0. For any set X, the identity function 1 X: X → X, 1 X (x) = x is bijective. The function f: R → R, f(x) = 2x + 1 is bijective, since for each y there is a unique x = (y − 1)/2 such that f(x) = y.