Comments (3)
mark-mediware
commented on August 15, 2024
@wiekern Not sure if it helps you, but I had similar errors and was pretty stuck. After some basic data analysis, I realized I had a few input variables with very limited distribution across groups (ex. Binary age bin with 10,000 rows = 0, and 5 rows = 1). After removing these variables/features, I had no errors.
Again, not sure if that's applicable to you, but was my (embarrassing ) issue.
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wiekern
commented on August 15, 2024
Thanks for your answer!
The distribution might not be the problem, that was my view. I am wondering if the regression model supports input with string like in my case column of "text". I am think of I must be convert text into a numeric value or word embeddings (vector).
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umangdadhaniya
commented on August 15, 2024
model = sm.logit('Result ~ Year + Amount_Spent + Popularity_Rank', data = train_data).fit()
Traceback (most recent call last):
File "", line 1, in
model = sm.logit('Result ~ Year + Amount_Spent + Popularity_Rank', data = train_data).fit()
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py", line 1963, in fit
bnryfit = super().fit(start_params=start_params,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py", line 227, in fit
mlefit = super().fit(start_params=start_params,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\base\model.py", line 519, in fit
xopt, retvals, optim_settings = optimizer._fit(f, score, start_params,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\base\optimizer.py", line 215, in _fit
xopt, retvals = func(objective, gradient, start_params, fargs, kwargs,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\base\optimizer.py", line 327, in _fit_newton
callback(newparams)
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py", line 211, in _check_perfect_pred
raise PerfectSeparationError(msg)
PerfectSeparationError: Perfect separation detected, results not available
model = sm.logit('Result ~ Year + Amount_Spent + Popularity_Rank', data = train_data).fit()
Traceback (most recent call last):
File "", line 1, in
model = sm.logit('Result ~ Year + Amount_Spent + Popularity_Rank', data = train_data).fit()
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py", line 1963, in fit
bnryfit = super().fit(start_params=start_params,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py", line 227, in fit
mlefit = super().fit(start_params=start_params,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\base\model.py", line 519, in fit
xopt, retvals, optim_settings = optimizer._fit(f, score, start_params,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\base\optimizer.py", line 215, in _fit
xopt, retvals = func(objective, gradient, start_params, fargs, kwargs,
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\base\optimizer.py", line 327, in _fit_newton
callback(newparams)
File "C:\Users\UMANG\anaconda3\lib\site-packages\statsmodels\discrete\discrete_model.py", line 211, in _check_perfect_pred
raise PerfectSeparationError(msg)
PerfectSeparationError: Perfect separation detected, results not available
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Related Issues (20)
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