AsadiAhmad/DBSCAN
DBSCAN is clustering algorithm.
DBSCAN helps organize unlabelled data points into distinct groups based on their density. You provide a dataset of observations, and it outputs a visualization showing which data points belong to which cluster, with 'noise' points identified. This is useful for data analysts, researchers, or anyone needing to discover natural groupings within their data.
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Use this if you need to find clusters of varying shapes and sizes in your data without knowing how many groups there should be beforehand, and you want to identify outliers.
Not ideal if your data has wildly varying densities, or if you strictly need a specific number of clusters identified.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Jan 06, 2025
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