[HN Gopher] Machine Learning Model Homotopy
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       Machine Learning Model Homotopy
        
       Author : jmount
       Score  : 63 points
       Date   : 2024-09-17 21:29 UTC (5 days ago)
        
 (HTM) web link (win-vector.com)
 (TXT) w3m dump (win-vector.com)
        
       | djoldman wrote:
       | References:
       | 
       | https://github.com/WinVector/Examples/blob/main/Model_Homoto...
        
         | disgruntledphd2 wrote:
         | Yeah the GitHub link is the meat of the article. Funny stuff. I
         | also would have assumed that the estimates wouldn't vary as
         | much, naively.
        
       | orimirs wrote:
       | Is the title wrong? No mentions of homologies in the link
        
         | disgruntledphd2 wrote:
         | Follow the GitHub link.
        
         | HeatrayEnjoyer wrote:
         | The title changed
        
       | bbstats wrote:
       | The grammar in this makes it pretty hard to follow
        
       | esafak wrote:
       | Looks like the start of an interesting article. Needs
       | development.
        
       | yldedly wrote:
       | Do you still see such dynamics in the coefficients if you have an
       | order of magnitude more data or fewer dimensions? 100 points in
       | 6D is not much even for linear regression, the model might just
       | be too high variance to interpolate monotonically between the two
       | populations.
        
         | jmount wrote:
         | The amount of data rapidly factors-out. One cat get the effect
         | even for millions of points in 6d. It is the complexity of the
         | model solution which is going to be degree D-1 polynomials over
         | a shared degree D-1 denominator that drive the effect.
        
           | mnky9800n wrote:
           | I may be misunderstanding, but wouldn't you see this effect
           | any time you did a k fold cross validation?
        
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       (page generated 2024-09-22 23:00 UTC)