Closed yang911113 closed 4 years ago
Hmm, hard to know without further details. Can you share the dataset and your code?
Hmm, hard to know without further details. Can you share the dataset and your code?
Thank you so much for your reply!!! Seems it's a little hard to share files here, I will send the dataset and code to your email(alejandro.schuler@gmail.com).
Thanks again for your help!
Can you try LogNormal distribution? (* I'm not in the development team at all, just a fan)
from ngboost.distns import LogNormal model = NGBRegressor(Dist=LogNormal) model.fit(X, y)
Can you try LogNormal distribution? (* I'm not in the development team at all, just a fan)
from ngboost.distns import LogNormal model = NGBRegressor(Dist=LogNormal) model.fit(X, y)
Hi, Seems the result gets better when I use other distribution types, thanks for your suggestion!
Closing as this seems to be resolved
Hello professors, Recently, I try to use NGBoost to do house price prediction. But the result seems to be weird, it only slightly floats in a certain value. When I try to use another database, the result is still weird. eg: pred: 206223.15351660148 label: 122500.0 pred: 206220.01918655884 label: 87200.0 pred: 206220.01918655884 label: 71000.0 pred: 206219.86433928832 label: 103400.0 pred: 206219.51956425532 label: 151600.0 pred: 206219.57320352976 label: 103600.0 pred: 206223.1237039902 label: 97600.0 pred: 206229.75965149773 label: 430200.0 pred: 206219.86433928832 label: 105700.0 pred: 206219.72805080027 label: 189700.0 pred: 206226.0452579732 label: 229400.0 pred: 206231.08766741856 label: 186300.0 pred: 206221.73433743903 label: 173400.0 pred: 206226.6751202078 label: 133700.0 pred: 206221.75150650492 label: 235600.0 pred: 206226.66010173922 label: 319700.0 pred: 206231.47243177023 label: 177900.0 pred: 206219.206962057 label: 139100.0 pred: 206219.1570302272 label: 104700.0
I just use the default setting of NGBoost, do you have any suggestions to tune this problem?
Looking forward to your reply!
Thank you so much, Yang