A new approach of neural networks to time-varying database classification

The time-varying databases, whose data distribution are changed with time. This database is frequently observed in many application areas including manufacturing, financing, and marketing. Knowledge discovery in time-varying databases is an important subject of data mining technology. This paper presents a moving-window neural network classification algorithm that can effectively classify the time-varying databases. We derive the algorithm. The experiment demonstrates the effective of the presented algorithm.