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[D] Tsetlin Machines, anyone heard of it? (alien.top)

submitted 1 year ago by Loud-Consideration-2@alien.top to c/machinelearning@academy.garden

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Hi, T have very little experience with Logic based Al algorithms, and my understanding is these machines use propositional logic algorithms (which wasn't something I have come across before, even when I was in uni).

My experience is in statistical & neural based networks and can understand the pros and cons of those networks.

I am just trying to understand what is the advantage and disadvantages of logic based algorithms specifically Tsetlin Machines? Is this something that I should learn more about? What are some good resources?

Thanks

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[–] currentscurrents@alien.top 1 points 1 year ago

One key difference is that they are not trained with end-to-end optimization but rather a hand crafted learning rule. This rule has strong inductive biases that work well for small datasets with pre-extracted features, like tabular data.

Their big disadvantage (and this applies to logical/symbolic approaches in general) is that they don't work well with raw data. Even easy datasets like CIFAR10. The world is too messy for perfect logical rules; neural networks are able to capture this complexity, but simpler models struggle to.

statistical

Note that learning is a fundamentally statistical process, so Tsetlin Machines are also statistics based.