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

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