| |
Ensemble averaging is one of the simplest types of committee machines. Along with boosting, it is one of the two major types of static committee machines.
Breiman (1996) suggested using the bootstrap sampling technique to train multiple models for ensemble averaging (in his case the models were decision trees, but the conclusions carry over to other models), a technique he refers to as bagging.
 See also: Knowledge, Neural network, Classification, Percept, Estimation
  
|
RSS
