Sandy4321

yes the question is better documentation for how to configure various vw options in Python? it would be great to have full example from start to end for python quantile...

I was able to find very limited examples in python this one https://vowpalwabbit.org/tutorials/python_first_steps.html is very concise

at least something like this , but for quantile regression https://pypi.org/project/vowpalwabbit/ >>> import numpy as np >>> from sklearn import datasets >>> from sklearn.model_selection import train_test_split >>> from vowpalwabbit.sklearn_vw import...

by the way in this link https://pypi.org/project/vowpalwabbit/ there is line at the bottom python/examples : example python code and jupyter notebooks to demonstrate functionality may you clarify how to find...

all right I found this folder then it would be great to share example for quantile regression in this style https://github.com/VowpalWabbit/vowpal_wabbit/blob/master/python/examples/poisson_regression.ipynb

in this link https://vowpalwabbit.org/docs/vowpal_wabbit/python/latest/vowpalwabbit.sklearn.html#vowpalwabbit.sklearn_vw.VWRegressor I see no example though there is example for classifier

Would a general tutorial about how to pass options to VW when using in Python in pyvw / scikit modes make sense here @Sandy4321, or alternatively a tutorial that explores...

even stackoverflow can not help https://stackoverflow.com/questions/44298795/one-time-vs-iteration-model-in-vowpal-wabbit-with-lrq-option

great thanks for help then lrq='um4' is not related to loss_function='quantile' in model = VW(convert_to_vw=False, lrq='um4', lrqdropout=True, loss_function='quantile') my guess also regularization or L1 or L2 may be added to...

great idea