A Review of Computational Methods for Clustering Genes with Similar Biological Functions <s> Clustering Techniques Optimization for Objective Function of Partitioning Clustering Techniques Clustering Validation <s> Kmeans is one of the most-efficient hard-clustering algorithms. It has been successfully applied to a number of problems. However, the efficiency of kmeans is dependent on its initialization of cluster centres. Different swarm intelligence techniques are applied for clustering problem. In this work, we have considered Ant Lion Optimization (ALO) which is a stochastic global optimization models. In this work Kmeans has been integrated with ALO for optimal clustering. The statistical measures of different performance metrics has been calculated and compared. The proposed method performs preferably better than Kmeans and PSO-Kmeans in terms of sum of intracluster distances and F-measure. <s> BIB001 </s> A Review of Computational Methods for Clustering Genes with Similar Biological Functions <s> Clustering Techniques Optimization for Objective Function of Partitioning Clustering Techniques Clustering Validation <s> Abstract K-Means is a popular cluster analysis method which aims to partition a number of data points into K clusters. It has been successfully applied to a number of problems. However, the efficiency of K-Means depends on its initialization of cluster centers. Different swarm intelligence techniques are applied to clustering problem for enhancing the performance. In this work a hybrid clustering approach based on K-means and Ant Lion Optimization has been considered for optimal cluster analysis. Ant Lion Optimization (ALO) is a stochastic global optimization model. The performance of the proposed algorithm is compared against the performance of K-Means, KMeans-PSO, KMeans-FA, DBSCAN and Revised DBSCAN clustering methods based on different performance metrics. Experimentation is performed on eight datasets, for which the statistical analysis is carried out. The obtained results indicate that the hybrid of K-Means and Ant Lion Optimization method performs preferably better than the other three algorithms in terms of sum of intracluster distances and F-measure. <s> BIB002
Majhi and Biswal BIB001 BIB002 K-means clustering Ant Lion Optimization (ALO) 