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Reading the abstract alone, I have no idea whether it's talking about algorithmic trees or, like, the big brown things with small green bits.
by PoignardAzur 2y ago
Reading the abstract alone, I have no idea whether it's talking about algorithmic trees or, like, the big brown things with small green bits.
- vatys 2y agoI had the exact same reaction: biology or computers? The only hint I can see anywhere on the page is "Statistics > Machine Learning" above the abstract title. I really want it to be about actual biological trees being studied on the scale of forests growing with smooth edges over long periods of time, but I suspect that's not what it is about.
- bonoboTP 2y agoThere's also "Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)" Also, the very first sentence of the actual paper (after the abstract) is > Random forests (Breiman, 2001) have emerged as one of the most reliable off-the-shelf supervised learning algorithms [...] arxiv.org is overwhelmingly used for math and computer science papers, though not exclusively. The paper will also likely be submitted to a machine learning venue.
- ibgeek 2y agoBiological trees don’t make predictions. Second or third sentence contains the phrase “randomized tree ensembles not only make predictions.”
- visarga 2y agoEven single cells are able to sense and adapt to their environment. That is to recognize and react.
- mhuffman 2y agoIt's talking about these[0] [0]https://en.wikipedia.org/wiki/Random_forest https://en.wikipedia.org/wiki/Random_forest
- defjm 2y agoJeremy Howard has a great video explaining Random Forests: https://youtu.be/blyXCk4sgEg https://youtu.be/blyXCk4sgEg .
- krystofee 2y agoYou have to know some machine learning fundamentals to figure that out - “Random Forest” is a specific machine learning algorithm, which does not need a further explanation. To take it a step further, they should really not describe “Machine learning”, no, its not like the machine takes a book and learns, its a term.
- bigmadshoe 2y agoThe tree is an incredibly common data structure in computer science. Decision trees are well known. Random forests are ubiquitous in Machine Learning. Should the authors really have to dumb their paper down so people who don’t work in this domain avoid confusing it with work in arborism?