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Machine Learning: Difference between revisions
→Bias-Variance Tradeoff
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===Bias-Variance Tradeoff=== | ===Bias-Variance Tradeoff=== | ||
* Let <math>L_D(h)</math> be the true loss of hypothesis h | |||
: and <math>L_S(h)</math> be the true loss of hypothesis h | |||
* <math>L_D(h_s^*) = L_D(h_D^*) + [L_D(h_s^*) - L_D(h_D^*)]</math> | |||
* The term <math>L_D(h_D^*)</math> | |||
* The term <math>[L_D(h_s^*) - L_D(h_D^*)]</math> is called variance. | |||
* Larger hypothesis class will get smaller bias but larger variance. | |||
* Overfitting vs. underfitting | |||