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Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

4 votes
1 answer
144 views

Why do we approximate the joint in ELBO if we already have access to it?

I realized in variational inference, our goal is to approximate $p(z|x)$ with $q(z)$. So we minimize $KL(q(z) || p(z|x)) = \mathbb{E}_{z \sim q} log\frac{q(z)}{p(z|x)}$. We then manipulate, through so …
Addison's user avatar
  • 221
2 votes
1 answer
415 views

What do people typically do with positive log likelihood?

I have a probabilistic Machine Learning model that models the data distribution using a multivariate T distribution. This distribution can have density > 1, and so when I compute log likelihood of the …
Addison's user avatar
  • 221
2 votes
1 answer
344 views

Random performance of AUPRC

I've been trying to understand how to interpret what random performance would be for a model I have on the AUPRC score. By 'random performance' I mean the worst possible performance. Purely unintellig …
Addison's user avatar
  • 221