Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Generalized learning vector quantization (GLVQ) has been proposed in as a generalization of the simple competitive learning (SCL) algorithm. The main argument of GLVQ proposal is its superior insensitivity to the initial values of the ights (code vectors).   show that the distinctive characteristics of the definition of GLVQ disappear outside a small domain of applications. GLVQ becomes identical to SCL when either the number of code vectors grows or the size of the input space is large. Besides that, the behavior of GLVQ is inconsistent for problems defined on very small scale input spaces. The adaptation rules fluctuate beten performing descent and ascent searches on the gradient of the distortion function. >
['Ana Isabel González', 'Manuel Graña', "Alicia D'Anjou"]
I am writing a research paper on a idea An analysis of the GLVQ algorithm
[{"from": "human", "value": "I am writing a research paper on a idea An analysis of the GLVQ algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Generalized learning vector quantization (GLVQ) has been proposed in as a generalization of the simple competitive learning (SCL) algorithm. The main argument of GLVQ proposal is its superior insensitivity to the initial values of the ights (code vectors).   show that the distinctive characteristics of the definition of GLVQ disappear outside a small domain of applications. GLVQ becomes identical to SCL when either the number of code vectors grows or the size of the input space is large. Besides that, the behavior of GLVQ is inconsistent for problems defined on very small scale input spaces. The adaptation rules fluctuate beten performing descent and ascent searches on the gradient of the distortion function. >"}]