Show HN: How simple (but clever) algorithms can find label issues in datasets

playground.cleanlab.ai

3 points

4 years ago

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://github.com/cleanlab/cleanlab, which implements the algorithms described in https://arxiv.org/abs/1911.00068.

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://cleanlab.ai/blog/cleanlab-vizzy/

I’m happy to answer any questions related to Vizzy, cleanlab, or confident learning and data-centric AI in general!