I have applied Logistic regression and I want to pass the reference object manually
Algorithm Success
A 0.91
B 0.98
C 0.76
.
.
.
B 0.77
C 0.68
D 0.43
E 0.81
Code:
p1_logit_model=sm.MNLogit(group["Algorithm"], group["Success"].astype(float))
res_p1 = p1_logit_model.fit(full_output= True)
f.write(str(res_p1.summary2()))
Output:
Results: MNLogit
===============================================================
Model: MNLogit Pseudo R-squared: 0.104
Dependent Variable: algorithm AIC: 184.2255
Date: 2018-12-18 17:19 BIC: 194.2622
No. Observations: 55 Log-Likelihood: -87.113
Df Model: 0 LL-Null: -97.227
Df Residuals: 50 LLR p-value: nan
Converged: 1.0000 Scale: 1.0000
No. Iterations: 9.0000
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algorithm = 0 Coef. Std.Err. t P>|t| [0.025 0.975]
--------------------------------------------------------------
p1_less100ms 0.2326 0.5804 0.4008 0.6886 -0.9050 1.3702
--------------------------------------------------------------
algorithm = 1 Coef. Std.Err. t P>|t| [0.025 0.975]
--------------------------------------------------------------
p1_less100ms -6.3891 3.9519 -1.6167 0.1059 -14.1346 1.3565
--------------------------------------------------------------
algorithm = 2 Coef. Std.Err. t P>|t| [0.025 0.975]
--------------------------------------------------------------
p1_less100ms -0.3208 0.6488 -0.4943 0.6211 -1.5925 0.9510
--------------------------------------------------------------
algorithm = 3 Coef. Std.Err. t P>|t| [0.025 0.975]
--------------------------------------------------------------
p1_less100ms 0.2604 0.5776 0.4508 0.6521 -0.8716 1.3924
The Logit() by default assumes the last category ('E') as reference parameter to compare againest all, However, I want to pass the category MANUALLY eveytime
Can anyone help me with this