python - Error while using stastmodels' WLS: SVD did not converge -



python - Error while using stastmodels' WLS: SVD did not converge -

i've written algorithm cascaded boosting classifier using wls (weighted to the lowest degree squares regression) in statsmodels, , have been able run few times. used few hundred images , fine.

however, i'm using train model approximately 4000 images. i'm getting next error:

mkl error: parameter 4 wrong on entry dlascl. traceback (most recent phone call last): file "c:\users\app\documents\python scripts\gbc_carclassify.py", line 95, in <module> gentlebooster.train(x_train,y_train,100) file "c:\users\app\documents\python scripts\gentleboost_c_class.py", line 103, in train temp_g = sm.wls(y1, self.x, w).fit() # step 2(a)(ii) file "c:\users\app\anaconda\lib\site-packages\statsmodels\regression\linear_model.py", line 127, in fit self.pinv_wexog = pinv_wexog = np.linalg.pinv(self.wexog) file "c:\users\app\anaconda\lib\site-packages\numpy\linalg\linalg.py", line 1574, in pinv u, s, vt = svd(a, 0) file "c:\users\app\anaconda\lib\site-packages\numpy\linalg\linalg.py", line 1323, in svd raise linalgerror('svd did not converge') numpy.linalg.linalg.linalgerror: svd did not converge

what reason? haven't seen message before:

mkl error: parameter 4 wrong on entry dlascl.

it appears error caused line:

temp_g = sm.wls(y1, self.x, w).fit()

python numpy classification linear-regression training-data

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