Sciweavers

KDD
1998
ACM

Coactive Learning for Distributed Data Mining

14 years 3 months ago
Coactive Learning for Distributed Data Mining
Weintroducecoactive learning as a distributed learning approachto data miningin networkedand distributed databases. Thecoactive learningalgorithmsact on independent data sets and cooperatebycommunicatingtraining information, whichis usedto guidethe algorithms'hypothesisconstruction. Theexchangedtraining informationis limited to examplesandresponsesto examples.It is shownthat coactive learningcanoffer a solution to learningonverylarge data sets byallowingmultiplecoactingalgorithmsto learnin parallel onsubsetsof the data,evenif thesubsetsare distributed overa network.Coactivelearningsupportsthe construction of global concept descriptions evenwhenthe individual learning algorithmsare providedwithtraining sets having biasedclass distributions.Finally,the capabilitiesof coactive learningare demonstratedonartificial noisydomains,andon real worlddomaindata withsparseclass representationand unknownattribute values.
Dan L. Grecu, Lee A. Becker
Added 06 Aug 2010
Updated 06 Aug 2010
Type Conference
Year 1998
Where KDD
Authors Dan L. Grecu, Lee A. Becker
Comments (0)