🎓K-Means Clustering and Its Use Cases in the Security Domain

🔰 What is Clustering ?

  • Points in the same group are as similar as possible
  • Points in the different groups are as dissimilar as possible

📌 Why is Clustering Used?

📑 Types of Clustering?

  1. Exclusive Clustering (K-Means)
  2. Overlapping Clustering (C-Means)
  3. Hierarchical Clustering

🎯 Application of Clustering:

  • Clustering helps marketers improve their customer base and work on the target areas. It helps group people (according to different criteria such as willingness, purchasing power, etc.) based on their similarity in many ways related to the product.
  • Clustering helps in the identification of groups of houses based on their value, type, and geographical locations.
  • Clustering is used to study earth-quake. Based on the areas hit by an earthquake in a region, clustering can help analyze the next probable location where an earthquake can occur.

✍🏻 What is K-Means Clustering?

K-Means Clustering

👨🏻‍💻 Algorithm steps Of K Means —

Steps Of K-Means Algorithm

🧠 Advantages of K-Means Clustering :

🎯 Disadvantages of K-Means Clustering :

📑 Use Cases in the Security Domain

1. Identifying Crime Localities

Identifying Crime Localities

2. Crime Document Classification

Crime Document Classification

3. Delivery Store Optimization

4. Insurance and Fraud Detection

Insurance and Fraud Detection

5. Automatic Clustering of it alerts

Automatic Clustering of it alerts

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