第19页
ACMing (慎独)
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The main way to combat the curse of dimensionality is to make some assumptions about the nature of the data distribution (either p(y|x) for a supervised problem or p(x) for an unsupervised problem). 引自第19页
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ACMing对本书的所有笔记 · · · · · ·
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第10页 Unsuoervised Learning
Picking a model of the “right” complexity is called model selection, and will be disc...
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第16页
There are many ways to define such models, but the most important distinction is this: ...
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第19页
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第20页
Linear regression can be made to model non-linear relationships by replacing x with som...
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第21页 Logistic Regression
We can generalize linear regression to the (binary) classification setting by making tw...
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