How clustering algorithms Works

Clustering algorithm is an unsupervised Learning type

• Here we do not have any target or outcome variable to predict. Used for clustering population in different groups, which is widely used for segmenting customers in different groups for specific intervention. (unsupervised Learning).
• In this,the machine took’s at the various characteristics of the data set and find the similarity of the data
• Then Similar data point groups together. It is basically a collection of objects on the basis of similarity and dissimilarity between them. It is called measure of similarity
• For example-

• Some of the clustering methods are Density-Based Methods ,Hierarchical Based Methods , Partitioning Methods ,Grid-based Methods
• K means clustering algorithm is the one of the famous unsupervised clustering method

Happy reading :)

Image credits-

kunwar-vikrant/K-means-Agglomerative-DBSCAN-clustering-algorithms-on-Amazon-reviews-data-set