Comments (2)
Kurt-Liuhf
commented on May 17, 2024
Hi @TAOinfoWr, the problem is fixed. You can reinstall ThunderGBM and have a try. But notice that some hyper-parameters look like the default params even though they are not (e.g., tree depth). That's because when we save the model, we only save the trained GBDTs and the tree depth is already contained in the trained model. Thank you!
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TAOinfoWr
commented on May 17, 2024
it works ! thank you very much !
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Related Issues (20)
- FileNotFoundError: Could not find module 'c:\users\donald seger\miniconda3\envs\tensorflow\lib\site-packages\thundergbm-0.3.16-py3.8.egg\thundergbm\thundergbm.dll' (or one of its dependencies). Try using the full path with constructor syntax.
- Can you please answer issue #63?
- the Random Forest classifies everything to be 1 HOT 2
- Can you please answer issue #68?
- Is there a parameter to set "minimum samples per leaf" for Random Forest? HOT 1
- Why did you remove my issue? It is completely legit. HOT 1
- Please why are you removing my issue without any reason? HOT 1
- Debug Assertion Failed
- AttributeError: 'TGBMClassifier' object has no attribute 'save' HOT 1
- issue with saving and reloading model? HOT 2
- Please answer issue #75
- How to visualize the ThunderGBM? HOT 3
- random seed generator HOT 1
- Output of multi:softprob is probably wrong HOT 4
- Problems with random forest classifier when using more and deeper leaners
- Check failed: [max_elem + n_columns*(max_elem + 1) < 0x7fffffff] Max_values is too large to be transformed.请问这个问题怎么解决？ HOT 2
- Can the Negative Weights be Input? HOT 2
- Cuda 12
- can give whl package for 0.3.16 for windows?
- TGBMRegressor save_model raise error
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