Mean Shift Clustering in Machine Learning

The mean shift algorithm is a nonparametric clustering algorithm that does not require prior knowledge of the number of clusters. If you’ve never used the Mean Shift algorithm, this article is for you. In this article, I’ll take you through an introduction to Mean Shift clustering in Machine Learning and its implementation using Python.

Mean Shift Clustering

Mean Shift clustering is a nonparametric clustering algorithm that does not require any prior knowledge of the number of clusters. Below is the complete process of the Mean Shift algorithm:

  1. It starts by placing a circle centered on each sample
  2. Then for each circle, it calculates the mean of all the samples located in the circle
  3. Then it moves the circle so that it is centered on the mean
  4. Then it iterates the mean shift step until all of the circles stop moving
  5. Then it shifts the circles in the direction of the highest density until each circle reaches a maximum of local density
  6. Then all the instances whose circles have settled in the same place are assigned to the same cluster

Some of the features of this algorithm are like the DBSCAN clustering algorithm, like how it finds any number of clusters of any shape. But unlike the DBSCAN clustering algorithm, this algorithm tends to cut clusters into chunks when they have internal density variations.

It is not a popular clustering algorithm because it is not suitable while working with large datasets. I hope you now have understood what mean-shift clustering is in machine learning. Now in the section below, I will take you through its implementation using Python.

Mean Shift Clustering using Python

This clustering algorithm has only one important parameter which is known as the bandwidth, which is nothing but the radius of the circle. The scikit-learn library in Python provides the MeanShift() class which can be used to implement this algorithm. So below is how you can implement the mean shift clustering using Python:

Mean Shift Clustering in Machine Learning

You can use this algorithm for any kind of problem based on clustering, but always remember that it is not preferable with large datasets.

Summary

The mean shift algorithm is a nonparametric clustering algorithm that does not require prior knowledge of the number of clusters. It is not a popular clustering algorithm because it is not suitable while working with large datasets. I hope you liked this article on an introduction to the mean shift clustering algorithm and its implementation using Python. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
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