[HN Gopher] Climbing trees 1: what are decision trees?
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       Climbing trees 1: what are decision trees?
        
       Author : SchwKatze
       Score  : 41 points
       Date   : 2025-05-18 02:56 UTC (20 hours ago)
        
 (HTM) web link (mathpn.com)
 (TXT) w3m dump (mathpn.com)
        
       | jononor wrote:
       | I love decision trees. Conceptually simple, computational
       | efficient and giving very good results for a lot of tasks. I
       | especially use them on microcontroller grade system, via emlearn
       | - which converts scikit-learn models to embedded friendly C code.
       | 
       | These articles are a good and pretty comprehensive introduction.
       | I would have loved to have even more examples around the
       | bias/variance trade off for forests, it is a key concept that not
       | all practitioners have integrated.
        
         | AprilisKalends wrote:
         | Is there a tool to better to visualize them than like this
         | https://mathpn.com/_astro/weather_tree.GMStLECX_ZgpDEk.svg for
         | humans? I have tried graphviz or doing it in tex to ugly
         | outputs
        
           | mathisd wrote:
           | https://github.com/parrt/dtreeviz has several interesting
           | visualisation
        
           | clockwork-dev wrote:
           | I've been liking Explainable Boosting Machines lately (kind
           | of a cross between a GAM and a tree). They also have decision
           | trees. Haven't tested them in production yet but they're
           | pretty to look at.
           | 
           | [0] https://interpret.ml/docs/ebm.html [1]
           | https://interpret.ml/docs/dt.html
        
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