[TBD]Role of DBSCAN in machine learning

Introduction

Laymen explanation

Density-based spatial clustering of applications with noise (DBSCAN)is a well-known data clustering algorithm that is commonly used in data mining and machine learning. If you are interested to know its usage, this document helps.

Technical explanation

Based on a set of points (let’s think in a bidimensional space as exemplified in the figure), DBSCAN groups together points that are close to each other based on a distance measurement (usually Euclidean distance) and a minimum number of points. It also marks as outliers the points that are in low-density regions.

DBSCAN in action

Advantages

• What’s nice about DBSCAN is that you don’t have to specify the number of clusters to use it. All you need is a function to calculate the distance between values and some guidance for what amount of distance is considered “close”

• Clusters formed are arbitrary in shape contrary to vanilla k-means which forms only convex shape

• DBScan clustering efficiently handles outliers and noisy datasets.

• DBScan algorithm is good for anomaly detection data. It locates regions of high density that are separated from one another by regions of low density.

Challenges

• DBSCan Clustering can not efficiently handle high dimensional datasets

• DBScan clustering does not work very well for data points with varying density

Selecting hyperparameters(r and eps)

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Role in machine learning

This colab gives example where DBSCAN is able to cluster example non-convex shape where k-means and hierarchical models couldn't

Relevance with neural networks

Reference

https://en.wikipedia.org/wiki/DBSCAN

https://www.kdnuggets.com/2020/04/dbscan-clustering-algorithm-machine-learning.html

https://towardsdatascience.com/how-dbscan-works-and-why-should-i-use-it-443b4a191c80

https://www.geeksforgeeks.org/difference-between-k-means-and-dbscan-clustering/

https://images.app.goo.gl/Sz5t5iw2xdpBfybD8

https://www.researchgate.net/figure/Description-of-the-proposed-algorithm-ANN-artificial-neural-network-DBSCAN_fig3_328066898

https://images.app.goo.gl/RmFvgRswY7BFgBae7

https://colab.research.google.com/drive/1yYsmQV_JWJaGNd1M6XjOqWPKj1PufT-I?usp=sharing

https://www.analyticsvidhya.com/blog/2020/09/how-dbscan-clustering-works/

https://youtu.be/AxARUMZh0sk?t=1645