Clustering is a popular machine learning approach, and research on clustering is always a
hot spot. A cellular automata based clustering is proposed in this paper. Cellular automata is …

In this paper, a decimal first degree cellular automata (FDCA) based clustering algorithm is
proposed where clusters are created based on reachability. Cyclic spaces are created and …

Data clustering is a well studied problem, where the aim is to partition a group of data
instances into a number of clusters. Various methods have been proposed for the problem …

Clustering ensemble is an open proposition that aims to solve the limitation of a single
cluster algorithm on the diversity of data structures in data partitions. It obtains a consensus …

In order to solve the problem that the number of clusters needs to be specified artificially in
the partition clustering and hierarchical clustering methods, this paper proposes an adaptive …

The traditional K-means algorithm has been widely studied and applied in data analysis due
to its simplicity, efficiency and effectiveness. However, the traditional K-means algorithm …

E-healthcare is warm area of research and a number of algorithms have been applied to
classify healthcare data. In the healthcare field, a large amount of clinical data is generated …

In the last decade the amount of the stored data related to almost all areas of life has rapidly
increased. However, the overall process of discovering knowledge from data demands more …

Clustering algorithms are attracting much application interest due to the significant growth in
the rate of data generation. However, the high computational complexity of the existing …

In recent years, several cluster ensemble methods have been developed, but they still have
some limitations. They commonly use different clustering algorithms in both stages of the …