Clustering Introduction


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Originally published at: Clustering Introduction | Learn Data Science

We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is and unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of similar objects.

Outline:

– What is clustering?
– Types of clustering methods:
1. Centroid-based clustering
2. Connectivity-based clustering
3. Distribution-based clustering
4. Density-based clustering
– Clustering weaknesses

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