In the context of the EM algorithm, what is the role of the E-step?
Maximizing the log-likelihood function directly with respect to θ\thetaθ.
Calculating the conditional expectation of the log-likelihood of the complete data, given the observed data and current parameter estimates.
Estimating the missing values by simple imputation.
Updating the observed Fisher Information matrix.