Gaussian Mixture Models Clustering
At the beginning of the algorithm, you are taking an initial guess for the relevant parameters. Then in each iteration, in the E-step you are computing the responsibilities for all the given datapoints and in the M-step you are computing the weighted means and variances.

Since you are clustering the datapoints there is not training or test set. You just want to divide your dataset to two (or more) clusters.