Application of Rough Set Based Reduction for Network data set

The modern technologies in all the fields constantly generate a large amount of data. The data if it is represented in an understandable form will influence the real world in all respects. The tremendous increase in the data size makes the analysis of the data more tedious. Hence the retrieval of useful information using systems with human approach is essential in today’s scenario. Hence feature reduction using Quick reduct , an application of Rough set theory is used to reduce feature set size and identify the useful features based on semi-supervised learning. Particle swarm optimization is used for Quick reduct feature reduction process. The algorithm is applied for network data set.