C4.5 Competence Map: a Phase Transition-inspired Approach.
Nicholas Baskiotis and Michele Sebag
In: ICML 2004, 21st International Conference on Machine Learning, july 2004, Banff, Canada.
How to determine a priori wether a learning algorithm is suited to a learning problem instance is a major scientific and technological challenge.
A first step toward this goal,
inspired by the Phase Transition (PT) paradigm developed in
the Constraint Satisfaction domain, is presented in this paper.
Based on the PT paradigm, extensive and principled experiments
allow for constructing the Competence Map associated to a
learning algorithm, describing the regions where this algorithm
on average fails or succeeds.
The approach is illustrated on the long and widely used
C4.5 algorithm. A non trivial failure region in the
landscape of k-term DNF languages is observed and some interpretations are offered for the experimental
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Theory & Algorithms|
|Deposited By:||Michele Sebag|
|Deposited On:||29 December 2004|