toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Record Links
Author (up) Zhu, D. doi  openurl
  Title A hybrid approach for efficient ensembles Type Journal Article
  Year 2010 Publication Decision Support Systems Abbreviated Journal  
  Volume 48 Issue 3 Pages 480-487  
  Keywords Ensembles; Classification; Data Envelopment Analysis (DEA ); Stacking  
  Abstract An ensemble of classifiers, or a systematic combination of individual classifiers, often results in better classifications in comparison to a single classifier. However, the question regarding what classifiers should be chosen for a given situation to construct an optimal ensemble has often been debated. In addition, ensembles are often computationally expensive since they require the execution of multiple classifiers for a single classification task. To address these problems, we propose a hybrid approach for selecting and combining data mining models to construct ensembles by integrating Data Envelopment Analysis and stacking. Experimental results show the efficiency and effectiveness of the proposed approach.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ admin @ Zhu2010 Serial 4810  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: