Comments (3)
Hi ifserge, Stacknet does not currently support different dataset for individual model.
What you could do is :
- feed Stacknet with different datasets and different parameter config,
- get the level 1 output for each of these configurations
- aggregate all level1 outputs in one file (for train and test data)
- run a final Stacknet config with the level 1 aggregate
Hope this helps
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Thank you for the assist @goldentom42
Actually now there is a way to do it through python.
You should have a look at the python generic model .
If look inside lib/python
, for example PythonGenericRegressor0.py
in line 148
and line 168
you can add your own pre-processing of data. You could do a sub-selection or anything you want.
If you choose this method , bear in mind:
- You are limited to only python algorithms you have available in your system.
- Your data is loaded as sparse data. If you want to chance them to numpy you need to do
X.toarray()
- you need to apply the same preprocessing in both train and test (e.g. lines 148,168)
Hope that helps.
from stacknet.
@kaz-Anova, My bad I totally forgot about this great feature...
Congrats for your nice LB position in Zillow's competition!
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