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added lightning.KernelSVC (binary only) #176
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added lightning.KernelSVC
StrikerRUS edab901
simplify generated code
StrikerRUS 6d38616
simplify code
StrikerRUS a8d0def
Merge branch 'master' into kernelsvc
StrikerRUS c332833
address review comments
StrikerRUS 10a7e46
avoid zero feature norm
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Have no idea how to avoid zero norm 🙁
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What is the lighting's behavior for zero feature vector norm? Can we get away with the same logic that we use for Support Vector norm?
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It relies on scikit-learn code:
https://github.com/scikit-learn/scikit-learn/blob/95d4f0841d57e8b5f6b2a570312e9d832e69debc/sklearn/metrics/pairwise.py#L1169-L1173
https://github.com/scikit-learn/scikit-learn/blob/95d4f0841d57e8b5f6b2a570312e9d832e69debc/sklearn/preprocessing/_data.py#L1730
https://github.com/scikit-learn/scikit-learn/blob/95d4f0841d57e8b5f6b2a570312e9d832e69debc/sklearn/preprocessing/_data.py#L63-L78
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If I understand the logic correctly it does the same thing (falls back to 1.0), shall we do the same here?
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To be honest, I'm not sure that complicating generated code in a such way worth it...
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I'd say we should always prefer correctness even if it means a slightly more complex code. Btw, does it really become that complex? Especially considering that we reuse the expression (to_reuse=True) here. AST doesn't look bad at all. Thanks for implementing this! 👍
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Yeah, no doubt!
In languages which implement
to_reuse=True
it looks OK, but if they don't... Though, there are many other places where without caching code looks terrible.I thought about more elegant solution, but didn't come to any.
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Well, TBH, the existing solution looks more than good to me at least at this point 👍