timpiperseek
timpiperseek
Yes thank you, it also looks like it is gone for me to.
as a side note is it possible to pickle the model object or is the only option to use the saveNativeModel method? Just asking as using as a pickle object...
So the above error is gone, but I suspect that something is still wrong when training on large data sets of 100 million plus. But I cannot put a finger...
okay so I think I have found the issue on my end. It is all good now
Thanks @tomicapretto, I guess I am after the fixed effect coefficient with a marginal interpretation. This stack exchange [question ](https://stats.stackexchange.com/questions/365907/interpretation-of-fixed-effects-from-mixed-effect-logistic-regression) should help to understand where my head is at and...
Thanks, @tomicapretto I feel like my example was a poor choice and is confusing the question. So I will choose another example that hopefully will be clearer as to what...
Thanks @tomicapretto 1. You are correct that there was a mistake, I have now amended it. 2. I am happy to take your suggestion here and pass it through the...
yeah that is really close to what I am after. what do you mean by > If you need to, you could parse the AST represented by the non-lookup factors...
Oh that is absolutely awesome, thank you.
okay it seems to be an issue with the quantized pool. If I recreate the pool it seems to work. for example this works. ``` test_pool = Pool( data=X_test_pd, label=y_test,...