Performance Analysis and Benchmarking of Clustering Algorithms with gene datasets
Meskat Jahan, Mahmudul Hasan · 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT) · 2019
Clustering is the identification of similar data from a rough or scaled or transformed data and grouping into clusters. Cluster shows symmetry and asymmetry of data and its relations. In this paper, comparisons of three fuzzy clustering algorithms and two conventional clustering algorithms are represented. The analysis is conducted on four datasets which include three gene expression datasets. Here, clustering performance is evaluated using both internal and external validation measurements and an attempt for searching the optimum number of the cluster has taken. This analysis provides an effective way of selecting a suitable algorithm for a particular dataset among different hardcore and soft-core clustering approaches.