I'm working on the U3 submission and I have some questions about the uncertainty prediction part.
In the documentation he said:
"To get predictions for all 9 quantiles (median + 8 other ) we can simply multiply every median to a coefficient ; this coefficient was calculated per level by minimizing loss over the last 28 known days (public LB)."
But I didn't find any function relating to minimisation in his scripts; there are only the raw coefficients.
Does anyone know how did he makes the minization? Did he learn thanks to the public LB evaluation metric?
I also wonder why in some of his get_ratio() functions he go through log(qs/(1-qs)) with qs = [0.005,0.025,0.165,0.25, 0.5, 0.75, 0.835, 0.975, 0.995]
Hello,
I'm working on the U3 submission and I have some questions about the uncertainty prediction part.
In the documentation he said:
"To get predictions for all 9 quantiles (median + 8 other ) we can simply multiply every median to a coefficient ; this coefficient was calculated per level by minimizing loss over the last 28 known days (public LB)."
But I didn't find any function relating to minimisation in his scripts; there are only the raw coefficients. Does anyone know how did he makes the minization? Did he learn thanks to the public LB evaluation metric? I also wonder why in some of his get_ratio() functions he go through log(qs/(1-qs)) with qs = [0.005,0.025,0.165,0.25, 0.5, 0.75, 0.835, 0.975, 0.995]
Thanks in advance :)