Title :
Learning weights for the quasi-weighted means
Author_Institution :
Inst. d´´Investigacio en Intelligencia Artificial, CSIC, Barcelona, Spain
fDate :
10/1/2002 12:00:00 AM
Abstract :
We study the determination of weights for quasi-weighted means (also called quasi-linear means) when a set of examples is given. We consider first a simple case, the learning of weights for weighted means, and then we extend the approach to the more general case of a quasi-weighted mean. We consider the case of a known arbitrary generator f. The paper finishes considering the use of parametric functions that are suitable when the values to aggregate are measure values or ratio.
Keywords :
learning (artificial intelligence); matrix algebra; minimisation; learning; measure values; parametric functions; quasi-linear means; quasi-weighted means; ratio values; Aggregates; Artificial intelligence; Environmental economics; Fusion power generation; Intelligent robots; Knowledge based systems; Knowledge representation; Learning;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2002.803498