Title
How to Find Big-Oh in Your Data Set (and How Not to)
Abstract
The empirical curve bounding problem is defined as follows. Suppose data vectors X;Yare presented such that E(Y [i]) =?¥f (X[i]) where?¥f (x) is an unknown function. The problem is toanalyze X;Y and obtain complexity bounds O(g u (x))and\Omega\Gammag l (x)) on the function?¥ f (x).As no algorithm for empirical curve bounding can be guaranteed correct, we consider heuristics.Five heuristic algorithms are presented here, together with analytical results guaranteeing correctnessfor...
Year
DOI
Venue
1997
10.1007/BFb0052828
IDA
Keywords
Field
DocType
heuristic algorithm
Iterative refinement,Discrete mathematics,Heuristic,Combinatorics,Big O notation,Correctness,Heuristics,Mathematics,Bounding overwatch
Conference
Volume
ISSN
ISBN
1280
0302-9743
3-540-63346-4
Citations 
PageRank 
References 
5
0.48
5
Authors
3
Name
Order
Citations
PageRank
Catherine C. McGeoch126259.29
Doina Precup22829221.83
paul r cohen31927460.49