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PiML: Python Interpretable Machine Learning Toolbox
- kdlag 2y ago[flagged]
- setopt 2y agoPiML is also a common abbreviation for Physics-informed Machine Learning.
- svl7 2y ago[flagged]
- isoprophlex 2y agoAdd Dutch to the list. Two of my kids are of the age where yelling "piemel" all day is about the funniest thing to do...
- deleted 2y ago[deleted]
- jszymborski 2y agoTIL. I've only ever heard the term PINN (physics-informed neural networks) before.
- pragma_x 2y agoI misread that as "impenetrable" machine learning and thought: "Well, it's about time someone admitted it." Ironically, the low-code examples do a good job of making this space a little more approachable.
- deleted 2y ago[deleted]
- frakt0x90 2y agoVery Happy to see FIGS on the list. I almost got a chance to use it on a recent project but the csutomer in the end decided they valued accuracy over interpretability. I wonder if the recent KANs fit into this? They're more interpretable than other NN architectures. Also, Berkeley has had a few articles on interpretable methods (including FIGS) over the years but idk how they compare to what you've already implemented: https://bair.berkeley.edu/blog/2022/02/02/imodels/ https://bair.berkeley.edu/blog/2022/02/02/imodels/ https://bair.berkeley.edu/blog/2020/04/23/decisions/ https://bair.berkeley.edu/blog/2020/04/23/decisions/
- 3abiton 2y agoQRD on FIGS for the curious ones?
- frakt0x90 2y agoThis explains it better than I could: https://bair.berkeley.edu/blog/2022/06/30/figs/ https://bair.berkeley.edu/blog/2022/06/30/figs/
- bravura 2y agoPretty cool. So it greedily constructs an ensemble of trees from scratch. At each step, it takes the one decision that reduces the loss the most. That's a nice approximation for the most compact tree ensemble.
- abhgh 2y agoI have used a successor [1] of FIGS and my experience was that although the theory is elegant, their benchmarking was incomplete.This is something I would look out for if you are planning to use it on a real-world problem. Again, this is not to be negative about the paper, but there is a gap between the theory and practice. I had raised this as an issue [2] on their repo, but after a few exchanges didn't receive any response. If you look at the last comment on that issue thread, you will see that Random Forest with proper hyperparam. search produces competitive results. [1] https://proceedings.mlr.press/v162/agarwal22b.html https://proceedings.mlr.press/v162/agarwal22b.html [2] https://github.com/csinva/imodels/issues/129 https://github.com/csinva/imodels/issues/129
- melenaboija 2y agoIs the source code available?
- zwaps 2y agoAm i blind? Where is the code?
- deleted 2y ago[deleted]
- dagw 2y agoLooks like they haven't actually published the source code, despite both GitHub and PyPI claiming the project is apache licensed. If you install the package all you get in the wheel is precompiled cython libraries and the absolute minimum python code needed to import them.
- mrks_hy 2y agoGiven the broader state of the Python ecosystem, that is a red flag for me. Why would you add an OSS license but withhold the sourcecode? The only reason I can think of is to "trick" people into downloading and betting that no-one actually checks the source, then hiding something in the .so files that are shipped as wheels. Tread carefully.
- Labo333 2y agoIndeed, this is a major blocker. I am very wary of installing it and would never ship this to production.
- maaaaattttt 2y agoThat’s a name that won’t go unnoticed by the german speaking colleagues.
- haustlauf 2y agoAs well as the Dutch ones.
- j7c6 2y agoI just pitched "Product Information Management Machine Learning" to my team lead ;) Which, in my opinion, is largely underestimated in that field of software... Maybe we should consider a different name though
- starbugs 2y agoPlease explain for international audiences :)
- B0073D 2y agoIt's very close to a word for male genitalia https://en.wiktionary.org/wiki/Pimmel https://en.wiktionary.org/wiki/Pimmel
- fleischhauf 2y agoyou will be also interested to be reading about PMML: https://en.m.wikipedia.org/wiki/Predictive_Model_Markup_Language https://en.m.wikipedia.org/wiki/Predictive_Model_Markup_Lang...