Discovering Trends in Large Datasets Using Neural Networks

Abstract

A novel knowledge discovery technique using neural networks is presented. A neural network is trained to learn the correlations and relationships that exist in a dataset. The neural network is then pruned and modified to generalize the correlations and relationships. Finally, the neural network is used as a tool to discover all existing hidden trends in four different types of crimes (murder, rape, robbery, and auto theft) in US cities as well as to predict trends based on existing knowledge inherent in the network.