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HDBSCAN, Fast Density Based Clustering, the How and the Why - John Healy
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PyData NYC 2018
HDBSCAN is a popular hierarchical density based clustering algorithm with an efficient python implementation. In this talk we show how it works, why it works and why it should be among the first algorithms you use when exploring a new data set. Further we will show how we took an inherently O(n^2) algorithm and turned it into the O(nlogn) algorithm that is available in scikit-learn-contrib.
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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
HDBSCAN is a popular hierarchical density based clustering algorithm with an efficient python implementation. In this talk we show how it works, why it works and why it should be among the first algorithms you use when exploring a new data set. Further we will show how we took an inherently O(n^2) algorithm and turned it into the O(nlogn) algorithm that is available in scikit-learn-contrib.
===
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
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