Stochastic Outlier Selection
Read OriginalThis technical blog article by Jeroen Janssens explains Stochastic Outlier Selection (SOS), a machine learning algorithm for outlier detection. It details how SOS works by transforming data into a dissimilarity matrix, computing affinities and binding probabilities, and outputting an outlier probability for each point. The article discusses its relation to t-SNE, its perplexity parameter, and includes a link to a Python implementation.
Comments
No comments yet
Be the first to share your thoughts!
Browser Extension
Get instant access to AllDevBlogs from your browser
Top of the Week
1
The Beautiful Web
Jens Oliver Meiert
•
2 votes
2
When your coding agent doesn’t understand your project, you’ll get junk
Benjamin Cane
•
1 votes
3
LLM Use in the Python Source Code
Miguel Grinberg
•
1 votes
4
Wagon’s algorithm in Python
John D. Cook
•
1 votes
5
An example conversation with Claude Code
Dumm Zeuch
•
1 votes