Practical tips for when and how to use quantile regression in machine learning
Great post as usual.
I have a question though. It seems to me that you are running different models for each quantile and therefore the quantile crossing might occur. What about the idea of Meinshausen 2006 https://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf.
This is just running 1 model, but still being able to calculate quantiles. Any feeling of pros and cons of one approach vs the other?
Many thanks for the great work.
Joan
Great, pratical stuff as always. Sharing with my entire DS team.
Potentially dumb question 😬 Would you use quantile regression to replace the news vendor problem optimization approach? Or as a compliment? I have a sense they are complimentary, but wondering how you would describe it. Thanks for sharing this :)
Great post as usual.
I have a question though. It seems to me that you are running different models for each quantile and therefore the quantile crossing might occur. What about the idea of Meinshausen 2006 https://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf.
This is just running 1 model, but still being able to calculate quantiles. Any feeling of pros and cons of one approach vs the other?
Many thanks for the great work.
Joan
Great, pratical stuff as always. Sharing with my entire DS team.
Potentially dumb question 😬 Would you use quantile regression to replace the news vendor problem optimization approach? Or as a compliment? I have a sense they are complimentary, but wondering how you would describe it. Thanks for sharing this :)