Finite Mixture Models for binary data

The algorithm is covered in depth on our overleaf page

Notation Mapping for Python

This connects the variables in the overleaf page to variables used in python. Everything is 0-based indexed and classes are labeled 0,1,2,3...num_classes

• X stays the same with the same shape

• Theta -> theta_params. Same shape

• k -> class_assignments

• pi -> class_probabilities

• squiggly pi -> class_membership_scores

• n_c -> num_members_per_class

• n_cj -> num_correct_per_class_by_q

• [alpha,beta] -> theta_hyperparams

• [alpha_c] -> class_prob_hyperparams