작업형3 범주형 변수 관련 질문

[퇴근후딴짓] 빅데이터 분석기사 실기 (작업형1,2,3)

예시문제 작업형3(신 버전) 🆕 updated 2023.11 / 로지스틱 회귀

해결된 질문

23.11.27 22:52 작성

411

선생님 안녕하세요!작업형3 로지스틱 회귀모형을 진행할 때범주형 데이터는 C()로 묶어서 하라고 말씀해주셨는데, 강의에서 만약 범주형 데이터인지 헷갈린다면 모두 C()로 묶어서 하라고 하셨던 것으로 기억하는데그렇게하면 에러가 뜨는데 왜일까요??

# 2.
# 로지스틱 회귀모형
from statsmodels.formula.api import logit
# model = logit('Survived ~ C(Gender) + C(SibSp) + C(Parch) + C(Fare)', data=df).fit() --> error
# print(df.head())
model = logit('Survived ~ C(Gender) + SibSp + Parch + Fare', data=df).fit()
print(model.summary())
# print(model.params['Parch'])
# 답 : -0.201

Warning: Maximum number of iterations has been exceeded.
         Current function value: inf
         Iterations: 35
Makefile:6: recipe for target 'py3_run' failed
make: *** [py3_run] Error 1
/usr/local/lib/python3.9/dist-packages/statsmodels/discrete/discrete_model.py:1819: RuntimeWarning: overflow encountered in exp
  return 1/(1+np.exp(-X))
/usr/local/lib/python3.9/dist-packages/statsmodels/discrete/discrete_model.py:1872: RuntimeWarning: divide by zero encountered in log
  return np.sum(np.log(self.cdf(q*np.dot(X,params))))
Traceback (most recent call last):
  File "/goorm/Main.out", line 26, in <module>
    model = logit('Survived ~ C(Gender) + C(SibSp) + C(Parch) + C(Fare)', data=df).fit()
  File "/usr/local/lib/python3.9/dist-packages/statsmodels/discrete/discrete_model.py", line 1983, in fit
    bnryfit = super().fit(start_params=start_params,
  File "/usr/local/lib/python3.9/dist-packages/statsmodels/discrete/discrete_model.py", line 230, in fit
    mlefit = super().fit(start_params=start_params,
  File "/usr/local/lib/python3.9/dist-packages/statsmodels/base/model.py", line 579, in fit
    Hinv = np.linalg.inv(-retvals['Hessian']) / nobs
  File "<__array_function__ internals>", line 5, in inv
  File "/usr/local/lib/python3.9/dist-packages/numpy/linalg/linalg.py", line 545, in inv
    ainv = _umath_linalg.inv(a, signature=signature, extobj=extobj)
  File "/usr/local/lib/python3.9/dist-packages/numpy/linalg/linalg.py", line 88, in _raise_linalgerror_singular
    raise LinAlgError("Singular matrix")
numpy.linalg.LinAlgError: Singular matrix

python 머신러닝 빅데이터 pandas 빅데이터분석기사

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