Mora Jiménez, InmaCid Sueiro, Jesús2009-07-292009-07-292009-07-291045-9227http://hdl.handle.net/10115/2589In this paper, we analyze stochastic gradient learning rules for posterior probability estimation using networks with a single layer of weights and a general nonlinear activation function. We provide necessary and sufficient conditions on the learning rules and the activation function to obtain probability estimates. Also, we extend the concept of well-formed cost function, proposed by Wittner and Denker, to multiclass problems, and we provide theoretical results showing the advantages of this kind of objective functions.enAtribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/Telecomunicacionesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess3325 Tecnología de las Telecomunicaciones5801 Teoría y Métodos Educativos