Python help with EM algorithm

To compute it, we basically: compute its probability under cluster model c normalize it to sum to 1 using its probabilities from all the clusters Finally we should return r after computing it. In [ ]: def expectation(self): # REPLACE THIS WITH THE ACTUAL r_ic COMPUTATION r = np.zeros((self.n, self.k)) return r EMModel.expectation = expectation Now we define the "maximization" step in the maximization function. This function's job is to take the previously computed lic and update the parameters Mc, Ec of each cluster distribution. This is done as follows: Here, N = EN Basically you should re-compute mu , sigma and pi using the previously computed r as per the given formulas. In [ ]: def maximization(self, r): self.mu = [] self.sigma = [] self.pi = [] # PLEASE ADD THE ACTUAL PARAMETERS COMPUTATION HERE. SET self.mu, self.sigma and self.pi TO THE CORRECT VALUES EMModel.maximization = maximization To compute it, we basically: compute its probability under cluster model c normalize it to sum to 1 using its probabilities from all the clusters Finally we should return r after computing it. In [ ]: def expectation(self): # REPLACE THIS WITH THE ACTUAL r_ic COMPUTATION r = np.zeros((self.n, self.k)) return r EMModel.expectation = expectation Now we define the "maximization" step in the maximization function. This function's job is to take the previously computed lic and update the parameters Mc, Ec of each cluster distribution. This is done as follows: Here, N = EN Basically you should re-compute mu , sigma and pi using the previously computed r as per the given formulas. In [ ]: def maximization(self, r): self.mu = [] self.sigma = [] self.pi = [] # PLEASE ADD THE ACTUAL PARAMETERS COMPUTATION HERE. SET self.mu, self.sigma and self.pi TO THE CORRECT VALUES EMModel.maximization = maximization