Prediction and Analysis of Rare Symptoms Using Association Rule Mining in Health Care Data Without Tree Generation
摘要
The dataset components are the only thing that an effective pattern mining technique depends on. We present an effective rare pattern mining method independent of the tree structure. Instead of using a tree structure to store and manage the dataset components, we used an array structure table and hash map. The suggested method removes duplicate rare patterns, which expedites rule mining. Our research demonstrates that the suggested approach uses less memory and operates faster than other state-of-the-art approaches.