This information is usually of the form of a penalty for complexity, such as restrictions for smoothness or bounds on the vector space norm.

jjs のブックマーク 2009/09/18 19:08

<blockquote class="hatena-bookmark-comment"><a class="comment-info" href="https://b.hatena.ne.jp/entry/16108070/comment/jjs" data-user-id="jjs" data-entry-url="https://b.hatena.ne.jp/entry/s/en.wikipedia.org/wiki/Regularization_(mathematics)" data-original-href="https://en.wikipedia.org/wiki/Regularization_(mathematics)" data-entry-favicon="https://cdn-ak2.favicon.st-hatena.com/64?url=https%3A%2F%2Fen.wikipedia.org%2Fwiki%2FRegularization_(mathematics)" data-user-icon="/users/jjs/profile.png">Regularization (mathematics) - Wikipedia</a><ul class="comment-tag" style="list-style: none; margin: 0px;"><li style="float: left">[<a href="https://b.hatena.ne.jp/q/%22business%20inteligence%22">business inteligence</a>]</li><li style="float: left">[<a href="https://b.hatena.ne.jp/q/decision">decision</a>]</li><li style="float: left">[<a href="https://b.hatena.ne.jp/q/io">io</a>]</li><li style="float: left">[<a href="https://b.hatena.ne.jp/q/process">process</a>]</li></ul><br><p style="clear: left">This information is usually of the form of a penalty for complexity, such as restrictions for smoothness or bounds on the vector space norm.</p><a class="datetime" href="https://b.hatena.ne.jp/jjs/20090918#bookmark-16108070"><span class="datetime-body">2009/09/18 19:08</span></a></blockquote><script src="https://b.st-hatena.com/js/comment-widget.js" charset="utf-8" async></script>

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Regularization (mathematics) - Wikipedia

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The green and blue functions both incur zero loss on the given data points. A learned model can be induced to prefer the green function, which may generalize better to more points drawn from the un...

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