G - Physics – 06 – F
Patent
G - Physics
06
F
G06F 7/08 (2006.01) G06N 5/02 (2006.01)
Patent
CA 2179211
Efficient techniques for inducing rules used in classifying data items on a noisy data set. The prior-art IREP technique, which produces a set of classification rules by inducing each rule and then pruning it and continuing thus until a stopping condition is reached, is improved with a new rule-value metric for stopping pruning and with a stopping condition which depends on the description length of the rule set. The rule set which results from the improved IREP technique is then optimized by pruning rules from the set to minimize the description length and further optimized by making a replacement rule and a modified rule for each rule and using the description length to determine whether to use the replacement rule, the modified rule, or the original rule in the rule set. Further improvement is achieved by inducing rules for data items not covered by the original set and then pruning these rules. Still further improvement is gained by repeating the steps of inducing rules for data items not covered, pruning the rules, optimizing the rules, and again pruning for a fixed number of times. The fully-developed technique has the O(nlogn) running time characteristic of IREP, but produces rule sets which do a substantially better job of classification than those produced by IREP.
At&t Corp.
Kirby Eades Gale Baker
LandOfFree
Rule induction on large noisy data sets does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Rule induction on large noisy data sets, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Rule induction on large noisy data sets will most certainly appreciate the feedback.
Profile ID: LFCA-PAI-O-1823686