Parallel Attribute-Efficient Learning of Monotone Boolean Functions
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
A New Algorithm to Select Learning Examples from Learning Data
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Exact Learning when Irrelevant Variables Abound
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
Computational Aspects of Parallel Attribute-Efficient Learning
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Finding Relevant Variables in PAC Model with Membership Queries
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
On parallel attribute-efficient learning
Journal of Computer and System Sciences
| Hi-index | 0.00 |
We consider the problem of learning in the presence of irrelevant attributes in Valiant's PAC model (1984). In the PAC model, the goal of the learner is to produce an approximately correct hypothesis from random sample data. If the number of relevant attributes in the target function is small, it may be desirable to produce a hypothesis that also depends on only a small number of variables. Haussler (1988) previously considered the problem of learning monomials of a small number of variables. He showed that the greedy set cover approximation algorithm can be used as a polynomial-time Occam algorithm for learning monomials on r of n variables. A outputs a monomial on r(ln q+1) variables, where q is the number of negative examples in the sample. We extend this result by showing that there is a polynomial-time Occam algorithm for learning k-term DNF formulas depending on r of n variables that outputs a DNF formula depending on O(r/sup k/log/sup k/q) variables, where q is the number of negative examples in the sample. We also give a polynomial-time Occam algorithm for learning decision lists (sometimes called 1-decision lists) with k alternations.