What are the different types of Clustering Algorithms ? Its Applications and Usage

 

What is Clustering ?

Clustering is a technique in which unsupervised data are grouped together based on similarities These groups are mutually exclusive.

Clustering Algorithms

• Partitioned-based Clustering
  1. K-Means
  2. K-Median
  3. Fuzzy C-means
  
• Hierarchical Clustering
  4. Agglomerative
  5. Decisive
  
• Density-based Clustering
  6. DBSCAN

Why Clustering ?

1. Exploratory Data Analysis (EDA)
2. Summary Generation
3. Outlier Detection
4. Finding Duplicates
5. Pre-processing Step

Applications of Clustering

• Retail Marketing
  1. Identify buying patterns of customers
  2. Recommending new books/movies to the new cast
• Banking
  3. Fraud detection in credit card use
  4. Identifying clusters of customers
• Insurance
  5. Fraud detection in claims analysis
  6. Insurance risk of customers
• Publication
  7. Auto-categorizing news based on their content
  8. Recommending similar news articles
• Medicine
  9. Characterizing patient behavior
• Biology
  10. Clustering genetic markets to identify family ties