A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is compared with existing clustering Techniques such as K-Means clustering, Hierarchical clustering and SOM Clustering. The proposed technique is used to cluster an Earthquake dataset and the performance is compared with the other existing clustering technique. The experimental results show that the proposed clustering method demonstrated better results as compared to other clustering methods.
|Title of host publication||Not Known|
|Publication status||E-pub ahead of print - 23 Aug 2018|
|Event||8th International Conference on Cloud Computing, Data Science & Engineering (Confluence) - , India|
Duration: 11 Jan 2018 → 12 Jan 2018
|Conference||8th International Conference on Cloud Computing, Data Science & Engineering (Confluence)|
|Period||11/01/18 → 12/01/18|
- Self Organizing Map (SOM)
- Hierarchical Clustering and K-means clustering.