広告効果予測のための制約付きニューラルネットワーク学習方式

抄録

This paper proposes an algorithm of neural networks for an estimate of advertising effect. The basic premise under this algoritm is that the relationship between input and output is monotonic increase. The algorithm is useful for the domain like an estimate of advertising effect which only deficient data are available.
The experimental simulation shows that the algorithm builts a reasonable model for an estimate of advertising effect.