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In computational complexity theory, the set splitting problem is the following decision problem: given a family F of subsets of a finite set S, decide whether there exists a partition of S into two subsets S 1, S 2 such that all elements of F are split by this partition, i.e., none of the elements of F is completely in S 1 or S 2.
Therefore, the remaining 3-sets can be partitioned into two groups: n 3-sets containing the items u ij, and n 3-sets containing the items u ij '. In each matching pair of 3-sets, the sum of the two pairing items u ij +u ij ' is 44T+4, so the sum of the four regular items is 84T+4. Therefore, from the four regular items, we construct a 4-set in ...
An example merge sort is given in the illustration. It starts with an unsorted array of 7 integers. The array is divided into 7 partitions; each partition contains 1 element and is sorted. The sorted partitions are then merged to produce larger, sorted, partitions, until 1 partition, the sorted array, is left.
For example, if all input values are positive and bounded by some constant C, then B is at most N C, so the time required is (). This solution does not count as polynomial time in complexity theory because B − A {\displaystyle B-A} is not polynomial in the size of the problem, which is the number of bits used to represent it.
The most important basic example of a datatype that can be defined by mutual recursion is a tree, which can be defined mutually recursively in terms of a forest (a list of trees). Symbolically: f: [t[1], ..., t[k]] t: v f A forest f consists of a list of trees, while a tree t consists of a pair of a value v and a forest f (its children). This ...
Two disjoint sets. In set theory in mathematics and formal logic, two sets are said to be disjoint sets if they have no element in common. Equivalently, two disjoint sets are sets whose intersection is the empty set. [1] For example, {1, 2, 3} and {4, 5, 6} are disjoint sets, while {1, 2, 3} and {3, 4, 5} are not disjoint. A collection of two ...
equal(S 1 ', S 2 '): checks whether the two given sets are equal (i.e. contain all and only the same elements). hash(S): returns a hash value for the static set S such that if equal(S 1, S 2) then hash(S 1) = hash(S 2) Other operations can be defined for sets with elements of a special type:
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]