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Lime: Explaining the predictions of any machine learning classifier

27 mentions on Hacker News by 22 people: 7 stories, 20 comments · first 2016-04-21 · latest 2021-05-15

Mentions per year 27 mentions · busiest year 2017 (13)
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  1. …space of model explainability that merit at least a try. [0] https://github.com/slundberg/shap [1] https://github.com/marcotcr/lime
    comment by thegginthesky · 2021-05-15 · in ML model can classify sex from retinal photograph, clinicians can't
  2. …algorithm but a Generalized Additive Model (i.e. like GLM but Squared instead of Linear) [1] https://github.com/marcotcr/lime [2] https://github.com/slundberg/shap [3] https://github.com/interpretml/interpret
    comment by mratsim · 2020-01-12 · in The Case for Bayesian Deep Learning
  3. …research that addresses them. For example, there are post-hoc explainability algorithms like LIME ( https://github.com/marcotcr/lime ) that "explain" the classification decisions of machine learning models. The obvious alternative is to…
    comment by timkam · 2019-12-27 · in A Robot That Explains Its Actions
  4. …are widely used in production systems. It's time this "NNs are hard to understand" idea died. [1] https://github.com/marcotcr/lime
    comment by nl · 2019-06-08 · in Outrageously Large Neural Nets: Sparsely-Gated Mixture-of-Experts Layer (2017)
  5. E.g., lime: https://github.com/marcotcr/lime
    comment by dmichulke · 2018-04-23 · in You probably don't need AI/ML. You can make do with well written SQL scripts
  6. …based on this paper [3], is also notable. [1]: https://distill.pub/2018/building-blocks/ [2]: https://github.com/marcotcr/lime [3]: https://arxiv.org/abs/1602.04938
    comment by jamessb · 2018-03-26 · in It’s time for a digital protection agency
  7. …out at me in this article was the use of Lime to explain models - I hadn't heard of it before. https://github.com/marcotcr/lime For NLP tasks, it looks like what it does is selectively delete words from the input and check the classifier…
    comment by polm23 · 2018-01-25 · in How to solve most NLP problems: a step-by-step guide
  8. …models is a hot field: https://www.youtube.com/watch?v=KP7-JtFMLo4 https://arxiv.org/abs/1602.04938 https://github.com/marcotcr/lime
    comment by standyro · 2017-12-19 · in A friend of mine died and I didn't know because of algorithms
  9. …https://arxiv.org/pdf/1602.04938.pdf https://homes.cs.washington.edu/~marcotcr/blog/lime/ https://github.com/marcotcr/lime Anytime anyone makes snide HN comments like "oh you can't understand why neural networks make predictions" the…
    comment by nl · 2017-12-11 · in DeepVariant: Highly Accurate Genomes with Deep Neural Networks
  10. …black-box-type classifiers. See LIME [1] and older technique called "partial dependence" [2]. [1]: https://github.com/marcotcr/lime [2]: https://github.com/bgreenwell/pdp
    comment by nerdponx · 2017-11-09 · in Artificial Intelligence and the Resurgence of Physiognomy
  11. …to support the unique needs of AI startups What are "advanced simulation tools" ? something like https://github.com/marcotcr/lime ?
    comment by sandGorgon · 2017-08-16 · in Andrew Ng is raising a $150M AI Fund
  12. …all of them. DARPA should ask HN next time it wants to know about the current state of AI. [1] https://github.com/marcotcr/lime [2] https://arxiv.org/abs/1503.02531
    comment by nl · 2017-08-11 · in Inside Darpa’s Push to Make Artificial Intelligence Explain Itself
  13. Checkout LIME: https://github.com/marcotcr/lime presumably in this example when reviewing the test dataset you'd see the ocean light up more than the warships. E.g. Here is an example of a wolf (ship) detection system that is actually…
    comment by benjaminjackman · 2017-07-29 · in Thoughts on OpenAI, reinforcement learning, and killer robots
  14. You might be interested in this approach to explaining the predictions for any classifier. https://github.com/marcotcr/lime
    comment by codewithcheese · 2017-07-24 · in A Practical Guide to Tree-Based Learning Algorithms
  15. Model decision interpretation is a solved problem: https://github.com/marcotcr/lime
    comment by iridium5 · 2017-05-09 · in The Dark Secret at the Heart of AI
  16. Quick explanation here: https://github.com/marcotcr/lime#what-are-explanations
    comment by anewhnaccount2 · 2017-03-14 · in Training Differentiable Models by Constraining Their Explanations
  17. …and see what features are changing the output and by how much. This approach is called LIME, see https://github.com/marcotcr/lime
    comment by Houshalter · 2017-02-22 · in Saving 80% in 90 Seconds?
  18. …a recent d3 meetup the topic was discussed but we primarily noted its importance. Notes at [2]. [1] https://github.com/marcotcr/lime [2] https://docs.google.com/document/d/1o-DO65PEZShLuadyRd35PsTJ...
    comment by ludwigschubert · 2016-12-07 · in Experiments in Handwriting with a Neural Network
  19. This brings Lime [1] to mind. "Explaining the predictions of any machine learning classifier" [1] https://github.com/marcotcr/lime
    comment by iverjo · 2016-09-08 · in Explainable Artificial Intelligence (XAI) Darpa Funding
  20. LIME is a software to analyze any machine learning classifier https://github.com/marcotcr/lime , they have very good paper in KDD too http://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf
    comment by nshm · 2016-08-19 · in The Difference Between AI, Machine Learning, and Deep Learning