A Comparative study Between Fuzzy Clustering Algorithm and Hard Clustering Algorithm
This is an incremental study that compares existing clustering methods without introducing new techniques.
The paper conducted a comparative study between fuzzy clustering algorithms, such as Fuzzy C-means, and hard clustering algorithms, like K-means, to evaluate their performance in data clustering, but no specific results or numbers were provided.
Data clustering is an important area of data mining. This is an unsupervised study where data of similar types are put into one cluster while data of another types are put into different cluster. Fuzzy C means is a very important clustering technique based on fuzzy logic. Also we have some hard clustering techniques available like K-means among the popular ones. In this paper a comparative study is done between Fuzzy clustering algorithm and hard clustering algorithm