LDA Convergence Explained with a Dog Pedigree Model

“What if my a priori understanding of dog breed group distribution is inaccurate? Is my LDA model doomed?”

My wife asked.

Welcome back to part 2 of the series, where I share my journey of explaining LDA to my wife. In the previous blog post, we discussed how LDA works and how it can be understood as a dog pedigree model.

This time around, let’s dive into the iterative fitting process of LDA!

Part 1 (link):

  • How does LDA work?
  • How to explain LDA to a non-technical person?

Part 2 (We are here now!):

  • How does LDA improve iteratively?
  • How does LDA converge?
  • Bonus: Get your LDA cheatsheet here!

Part 3:

  • When to use LDA & when not to?
  • How can we use it in Python?
  • What are the alternatives & variants to LDAs (excluding LLMs)?

Let’s get started.

If you have not read part 1 of the series, I strongly encourage you to read it first, as we will build on that understanding.

Quick Recap from Part 1