Mle, Machine Learning Models, Maximum Likelihood, Logistic Regression, Practical Mle.
y): z = np.dot(X, theta) n_log_likelihood = -np.sum(y * z - np.log(1 + np.exp(z))) return n_log_likelihood Line 5: We calculate the linear combination coefficients θ and features X. Line 6: We calculate the negative likelihood function. Maximizing the likelihood function Now, we need to find the