AN ENHANCED ALGORITHM FOR IMPROVED CLUSTER GENERATION TO REMOVE OUTLIER’S RATIO FOR LARGE DATASETS IN DATA MINING
| Author(s) | : | Mayuri G. Vadgasiya, Prof. Jay M. Jagani |
| Institution | : | M.E. [Computer Engineering], Darshan Institute of Engineering & Technology, Rajkot |
| Published In | : | Vol. 1, Issue 11 — November 2014 |
| Page No. | : | 203-208 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
existing studies in data mining focus on Outlier detection on data with single clustering algorithm mostly.There are lots of methods available in data mining to detect the outlier by making the clusters of data and then detect theoutlier from them. Outlier can be reduced if we improve the clustering. The values or objects that are similar to eachother are organized in group it’s called cluster and the values or objects that do not comply with the model or generalbehavior of the data these data objects called outliers. Outliers detect by clustering. We make algorithm that will begenerate the percentage value of cluster and the outliers and its compulsory to total no of cluster percentage are greaterthan the total no of outlier percentage. If the cluster are not more than outliers then algorithm will be improved the totalno of cluster and reduce the outliers. The output of the algorithm will be generating total original objects. If the no ofinput objects and no of output objects are not same then we assume that some error occur in the algorithm.
Mayuri G. Vadgasiya, Prof. Jay M. Jagani, “AN ENHANCED ALGORITHM FOR IMPROVED CLUSTER GENERATION TO REMOVE OUTLIER’S RATIO FOR LARGE DATASETS IN DATA MINING”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 1, Issue 11, pp. 203-208, November 2014.
