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spr-lnl's Issues

numpy.linalg.LinAlgError: Singular matrix

I'm trying to use the SPR+SR (without CutMix) on my dataset, where noise rate is 30% and 50%. I noticed that after few epochs I see get this error

Traceback (most recent call last):
  File "/root/miniconda3/envs/key2med/lib/python3.10/multiprocessing/pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
  File "/root/SPR-LNL/models/spr.py", line 12, in linear
    H = np.dot(np.dot(X, np.linalg.inv(np.dot(X.T, X))), X.T)
  File "/root/miniconda3/envs/key2med/lib/python3.10/site-packages/numpy/linalg/linalg.py", line 561, in inv
    ainv = _umath_linalg.inv(a, signature=signature, extobj=extobj)
  File "/root/miniconda3/envs/key2med/lib/python3.10/site-packages/numpy/linalg/linalg.py", line 112, in _raise_linalgerror_singular
    raise LinAlgError("Singular matrix")
numpy.linalg.LinAlgError: Singular matrix

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/root/SPR-LNL/chex_main.py", line 216, in <module>
    clean_set = spr(args, ep_stats, clean_set) 
  File "/root/SPR-LNL/models/spr.py", line 151, in spr
    sub_set = res.get()
  File "/root/miniconda3/envs/key2med/lib/python3.10/multiprocessing/pool.py", line 774, in get
    raise self._value
numpy.linalg.LinAlgError: Singular matrix

My PCA dimensions are 10. Is it because the model asserts all labels as noisy?

The dataset I'm working on is internal with around 200k images and a binary classification task. And your approach is a potential baseline in our paper, I hope you get back soon :)

SPR identify noisy data

Hello author,
I trained my own data using the method in your paper, and I output all the noise data. I analyzed these noise data, but some of them were not very accurate. Although I achieved high accuracy through the method in the paper, it is based on removing too much data. I want to relax the standards for identifying noisy data, although it may reduce accuracy. What should I do? thanks

cutmix是必须的吗

我仔细研究了您的代码,发现当cutmix设置为0时,spr函数处理结果返回的clean_set并没有应用,在这种情况下,您的SPR-LNL算是没有实际应用到训练过程中吗?这个cutmix是必须设置为1的吗?为什么要这样呢?也有可能是我对代码的理解有误,希望能够得到您的解答,谢谢!

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