Measuring the Complexity of Classification Problems

9 years 11 months ago
Measuring the Complexity of Classification Problems
We studied a number of measures that characterize the difficulty of a classification problem. We compared a set of real world problems to random combinations of points in this measurement space and found that real problems contain structures that are significantly different from the random sets. Distribution of problems in this space reveals that there exist at least two independent factors affecting a problem's difficulty, and that they have notable joint effects. We suggest using this space to describe a classifier's domain of competence. This can guide static and dynamic selection of classifiers for specific problems as well as subproblems formed by confinement, projections, and transformations of the feature vectors.
Tin Kam Ho, Mitra Basu
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors Tin Kam Ho, Mitra Basu
Comments (0)