from sklearn.linear_model import LogisticRegression
from sklearn.datasets import make_classification

# Create a logistic regression estimator object
lr = LogisticRegression(random_state=42, C=0.1)

# Get the current parameters and their values
params = lr.get_params()
print(params)

# Fit the estimator to some data
X, y = make_classification(random_state=42)
lr.fit(X, y)

# Get the estimated coefficients and intercept
coefficients = lr.coef_
intercept = lr.intercept_
print(coefficients)
print(intercept)