An Efficient Algorithm for the Approximate Median Selection Problem
CIAC '00 Proceedings of the 4th Italian Conference on Algorithms and Complexity
| Hi-index | 0.00 |
In this paper we introduce a class of generalized sorting (ordering) problems called ''classifications.'' To each ''classification,'' we associate two quantities: informational entropy (average information quantity) and operational entropy (measure of computational complexity, that is, number of comparisons necessary to ''classify'' a given sequence of items). The relationship between these quantities is discussed. For a certain classification involving n items, its operational entropy is shown to be approximately n.log"2n although its informational entropy is constantly equal to 1, independent of the number of items n.