A fuzzified BRAIN algorithm for learning DNF from incomplete data

Computer Science – Information Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

Aim of this paper is to address the problem of learning Boolean functions from training data with missing values. We present an extension of the BRAIN algorithm, called U-BRAIN (Uncertainty-managing Batch Relevance-based Artificial INtelligence), conceived for learning DNF Boolean formulas from partial truth tables, possibly with uncertain values or missing bits. Such an algorithm is obtained from BRAIN by introducing fuzzy sets in order to manage uncertainty. In the case where no missing bits are present, the algorithm reduces to the original BRAIN.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A fuzzified BRAIN algorithm for learning DNF from incomplete data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A fuzzified BRAIN algorithm for learning DNF from incomplete data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A fuzzified BRAIN algorithm for learning DNF from incomplete data will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-372777

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.