On the learning of weights in some aggregation operators: the weigthed mean and OWA operators
On the learning of weights in some aggregation operators: the weigthed mean and OWA operators
We study the determination of weights for two types of aggregation operators: the weighted mean and the OWA operator. We assume that there is at our disposal a set of examples for which the outcome of the aggregation operator is known. In the case of the OWA operator, we compare the results obtained by our method with another one in the literature. We show that the optimal weighting vector is reached with less cost.
The author acknowledges partial support of the CICYT project SMASH (TIC96-1138-C04-04).
Peer reviewed
WOWA operators, Teoria de, :03 Mathematical logic and foundations::03E Set theory [Classificació AMS], Modeling, Weighted Mean, Conjunts, Teoria de, Modelling, Learning weights, Aggregation operators, Classificació AMS::03 Mathematical logic and foundations::03E Set theory, Learning weigths, OWA operators, Conjunts, Weighted mean
WOWA operators, Teoria de, :03 Mathematical logic and foundations::03E Set theory [Classificació AMS], Modeling, Weighted Mean, Conjunts, Teoria de, Modelling, Learning weights, Aggregation operators, Classificació AMS::03 Mathematical logic and foundations::03E Set theory, Learning weigths, OWA operators, Conjunts, Weighted mean
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!