logistic regression in Python

from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
# transform data
scaled_X_train = scaler.fit_transform(X_train)
scaled_X_test = scaler.transform(X_test)


from sklearn.linear_model import LogisticRegressionCV
log_model = LogisticRegressionCV(cv=5, random_state=101).fit(scaled_X_train, y_train)
log_model


log_model.C_


log_model.get_params()


log_model.coef_


coefs = pd.Series(index=X.columns,data=log_model.coef_[0])
coefs = coefs.sort_values()
plt.figure(figsize=(10,6))
sns.barplot(x=coefs.index,y=coefs.values);