Data Mining Clustering Techniques – A Review
vivek nailwal, shubham vashist, lisa gopal · Journal of Emerging Technologies and Innovative Research · 2019
Data mining is a modern technique in which the information of a large data set and make over into a resonable form for supplementary purposes. Clustering is a very important task in data mining application and data analysis. it is a specific operation that is used for arrangement a set of entity in the same cluster are more related to each other than to those in other cluster. data mining can be done in various phases.supervised and unsupervised learning is used in data mining. clustering is a unsupervised learning. A good clustering approach will make high remarkable group with similar data in intra-class and low inter-class similarity. Clustering algorithms can be classified into 4 parts such as- 1) hierarchical-based algorithms 2) partition based algorithm 3) grid-based algorithms 4) density-based algorithm. Partitioning clustering algorithm breaks the set of data points into k no of partition, where each partition represents a group or cluster. keywords-Clustering ,k-mean clustering, data mining ,supervised or unsupervised learning.