BAGGINGC

Bootstrapping and aggregation of classifiers

     W = BAGGINGC (A,CLASSF,N,ACLASSF,T)

Input
A	Training dataset.
CLASSF	The base classifier (default: nmc)
N	Number of base classifiers to train (default: 100)
ACLASSF	Aggregating classifier (default: meanc), [] for no aggregation.
T	Tuning set on which ACLASSF is trained (default: [], meaning use A)

Output
W	A combined classifier (if ACLASSF was given) or a stacked  classifier (if ACLASSF was []).

Description

Computation of a stabilised version of a classifier by bootstrapping and  aggregation ('bagging'). In total N bootstrap versions of the dataset A are generated and used for training of the untrained classifier CLASSF.  Aggregation is done using the combining classifier specified in CCLASSF.  If ACLASSF is a trainable classifier it is trained by the tuning dataset  T, if given; else A is used for training. The default aggregating classifier  ACLASSF is MEANC. Default base classifier CLASSF is NMC.

See also

datasets, mappings, nmc, meanc, boostingc,