Scalable Rough C-Means clustering using Firefly algorithm
Bala Krushna Tripathy, Abhilash Namdev · International Journal of Computer Science and business informatics/International journal of computer science and business informatics · 2016
Our main interest is in dealing with the disadvantages of old clustering algorithms and coming up with a method that can generate clusters which produce optimal results when compared with previous approaches. Firstly, our focus is on analyzing the limitations of most widely used clustering algorithm. Here we choose K means clustering algorithm for the purpose. To provide the optimal results from the initial stage of algorithm we use firefly algorithm. The bioinspired algorithm that generates optimal minimum or maximum values based on certain parameters. To avoid the strictness on the boundary area in k means algorithm, we choose Rough C means algorithm, which provide some flexibility during the clustering process. Our proposed method provides most efficiency both in terms of time and space. We used efficient data structures which help us to avoid waste of memory while computation and also our algorithm utilizes maximum resources of the machine to make the execution rate as fast as possible.