Discovery of Potential High Utility Itemset from Uncertain Database using Multi Objective Discrete Differential Evolutionary Algorithm

In this research, we use the Multi-Objective Discrete Differential Evolutionary Algorithm (MODDEA) method to efficiently mine the high utility itemset mining (HUIM) in a limited period based on the mining of potential high utility itemset from uncertain dataset. MODDE-based HUI miners use five key processes and two objective functions. Both fitness value and uncertainty probability of each item is given equal importance while mining Potential High Utility Itemset (PHUI) from uncertain dataset. The suggested approach is tested on the Retail Utility dataset, which is a real-world example. Utility threshold is not required to mine the PHUIs.