Show HN: How simple (but clever) algorithms can find label issues in datasets
2 by calebchiam | 0 comments on Hacker News.
I built Vizzy as a hackathon project, with the goal of explaining how relatively simple (but clever) algorithms can be a powerful tool to automatically find issues in datasets, including label errors and out-of-distribution data. Vizzy uses a JavaScript port of (a part of) https://ift.tt/436VWxO , which implements the algorithms described in https://ift.tt/GrAu8O7 . There are other neat technical nuggets in the implementation of Vizzy as well, including ML model training in the browser (using features from a pretrained ResNet-18, performing truncated SVD, and using an SVM model for speed). If you’re interested in the details of how Vizzy works, check out this blog post: https://ift.tt/HByjt3S I’m happy to answer any questions related to Vizzy, cleanlab, or confident learning and data-centric AI in general!
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