I am working on Logistic regression model and I am using statsmodels api's logit. I am unable to figure out how to feed interaction terms to the model.
You can use the formula interface, and use the colon,: , inside the formula, for example :
import statsmodels.api as sm
import statsmodels.formula.api as smf
import numpy as np
import pandas
np.random.seed(111)
df = pd.DataFrame(np.random.binomial(1,0.5,(50,3)),columns=['x1','x2','y'])
res1 = smf.logit(formula='y ~ x1 + x2 + x1:x2', data=df).fit()
res1.summary()
Logit Regression Results
==============================================================================
Dep. Variable: y No. Observations: 50
Model: Logit Df Residuals: 46
Method: MLE Df Model: 3
Date: Thu, 04 Feb 2021 Pseudo R-squ.: 0.02229
Time: 10:03:59 Log-Likelihood: -32.463
converged: True LL-Null: -33.203
Covariance Type: nonrobust LLR p-value: 0.6869
==============================================================================
coef std err z P>|z| [0.025 0.975]
------------------------------------------------------------------------------
Intercept -0.9808 0.677 -1.449 0.147 -2.308 0.346
x1 0.4700 0.851 0.552 0.581 -1.199 2.139
x2 0.9808 0.863 1.137 0.256 -0.710 2.671
x1:x2 -1.1632 1.229 -0.946 0.344 -3.572 1.246
==============================================================================