4 Clustering Model Algorithms in Python and Which is the Best

K-means, Gaussian Mixture Model (GMM), Hierarchical model, and DBSCAN model. Which one to choose for your project?

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In this tutorial, we will talk about four clustering model algorithms, compare their results, and discuss how to choose a clustering algorithm for a project. You will learn:

• What are the different types of clustering model algorithms?
• How to run K-means, Gaussian Mixture Model (GMM), Hierarchical model, and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) model in Python?
• How to use PCA (Principal Component Analysis) and t-SNE (t-distributed stochastic neighbor embedding) for dimensionality reduction and visualization?
• How to utilize clustering model results for the business?
• How to select a clustering model algorithm for your project?

Resources for this post:

• Video tutorial for this post on YouTube
• Python code is at the end of the post. Click here for the Colab notebook.
• More video tutorials on clustering models
• More blog posts on clustering models

Let’s get started!

Step 0: Clustering Model…