From the course: Data Science Foundations: Data Mining in Python
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DBSCAN - Python Tutorial
From the course: Data Science Foundations: Data Mining in Python
DBSCAN
- [Instructor] The final method of clustering that I want to show you is called DBSCAN for density-based spatial clustering of applications with noise. It's a very long name but what DBSCAN is really good for is when you don't have nice, tight little spherical or at least convex groups. When you have groups, for instance, that are in circles or rings or they have irregular shapes. DBSCAN does this by building up from individual neighbors and really doing an accretion to get a cluster. It also can leave certain points out, it's saying this one appears to be noise. Let's see how this works with the penguins dataset. We do this by loading a number of libraries and functions, including DBSCAN from the scikit-learning library. I'm going to read the dataset from the local CSV file and as before, I'm going to read the data from the local CSV file, separate the class variable into y, standardize the other measurements and…
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