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I'd argue that you're too restrictive in your definition. e.g. unsupervised clustering has no sample training data. The usual definition (due to Mitchell) is t
by snotrockets 8y ago
I'd argue that you're too restrictive in your definition. e.g. unsupervised clustering has no sample training data.
The usual definition (due to Mitchell) is that machine learning is a system s.t. its performance on a given task improves by past experience.
- thegginthesky 8y agoActually, any unsupervised method, including clustering, still has training data. The only difference is it doesn't have a target y variable in the training set to minimize the error metric, hence the name unsupervised. But the definition you mention is right. Yet, any dataset that you use to fit your model will be your training set, even if you don't have a train test split or the like, because you used it to train your model over.
- snotrockets 8y agoK-means has no "training data" per se.