Optimize Prototype Classification Based on GA ANT Hybrid Technique

Abstract

Learning is the process of generating useful information from a huge volume of data. Learning can be classified as supervised learning and unsupervised learning. Classification is a kind of supervised learning and Clustering is a kind of unsupervised learning. Prototype clustering and classification is new technique in data mining. The prototype clustering and classification also called as ensemble clustering and classification. The Proposed novel method for prototype clustering and classification based on ant colony optimization and genetic algorithm. We conduct experiments with the prototype clustering and classification based on GA ANT hybrid technique using UCI repository with three data sets. The experimental results show that the proposed approach can achieve superior classification performance than other commonly used data mining approaches.