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Yes, "unlabeled" means that the examples are not marked as "true" or "false", and the "inferring" you are doing is making your function fit the data (e.g. minim
by astazangasta 11y ago
Yes, "unlabeled" means that the examples are not marked as "true" or "false", and the "inferring" you are doing is making your function fit the data (e.g. minimizing some error term). Life doesn't come with pre-packaged answers; humans use unsupervised learning.
- fallingfrog 11y agoRight, but we do have a reward function that says pleasurable/painful and novel/boring and probably other stuff too. So that can be viewed as a labeling on the data. Earlier data can be associated with the reward labeling through induction; that's how a recurrent neural net works. Doubtless that's an oversimplification though.