K-means clustering
The K-Means clustering algorithm, a commonly used clustering algorithm, is an iterative process used to minimize the distance of the data point from the average data point in the cluster.[1] The k-means algorithm is one of the fastest clustering algorithms available.[2] K-Means can group data only unsupervised based on the similarity of customers to each other.[3]
References
- ↑ 7 Innovative Uses of Clustering Algorithms in the Real Worlddatafloq.com
- ↑ KMeansscikit-learn.org
- ↑ Intro to k-MeansCoursera