huaxingao commented on issue #27337: [SPARK-30545][ML][PYSPARK] Impl Extremely 
Randomized Trees
URL: https://github.com/apache/spark/pull/27337#issuecomment-578382984
 
 
   @zhengruifeng 
   I took a quick look of how the random split is picked.
   
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.65.7485&rep=rep1&type=pdf
   
   
![image](https://user-images.githubusercontent.com/13592258/73117398-e18b4100-3ef9-11ea-80a6-09f94398e215.png)
   
   
   It seems to me that in the paper, the random threshold is found by sampling 
from the continuous uniform distribution [min(feature), max(feature)]. Seems to 
me that in your implementation, the random threshold is sampled uniformly (and 
discretely) from the set of possible splits generated by findSplits(). I know 
your way is simpler, but I am not sure if it is close enough to the original 
method in the paper. 

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