Comments (7)
代码如下:
x,y = load_svmlight_file("./thundergbm/dataset/test_dataset.txt")
clf = TGBMModel()
clf.fit(x,y)
y_predict=clf.predict(x,y)
print(y_predict)
from thundergbm.
Thanks for the feedback! We have fixed the problem. Please pull the latest code, recompile it, and run it again.
from thundergbm.
Thanks for the feedback! We have fixed the problem. Please pull the latest code, recompile it, and run it again.
新的代码预测结果全是0,感觉也不对啊
print(y_predict,y_predict.sum())
and the result return [0. 0. 0. ... 0. 0. 0.] 0.0
from thundergbm.
Would you share your machine environment (e.g., CUDA version, GPU, OS, etc.)? And dataset if you are not using test_dataset.txt
. This will help us reproduce the problem.
Also, please use English, so that other users in the community and contributors may help fix this issue.
from thundergbm.
CUDA Version 9.1.85, OS:ubuntu16.04, GPU1080Ti, and dataset is test_dataset.txt
.
from thundergbm.
CUDA Version 9.1.85, OS:ubuntu16.04, GPU1080Ti, and dataset is
test_dataset.txt
.
I have solved it, thanks a lot!
from thundergbm.
Sounds cool. If there is anything needed to be improved, please let us know or even better, contribute to the project :)
from thundergbm.
Related Issues (20)
- any status update on issue #63? HOT 1
- ImportError: cannot import name 'TGBMClassifier' from 'thundergbm' (unknown location)
- 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?
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- 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
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- 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
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- Cuda 12
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