Let The Problem Is Imin Fxsub1sub Xsub2sub Xsubnsubi Subject To #387
Let the problem is <i>min f(x<sub>1</sub>, x<sub>2</sub>, …, x<sub>n</sub>)</i> subject to <i>h<sub>1</sub>(x<sub>1</sub>, x<sub>2</sub>, …, x<sub>n</sub>) = 0</i>. And it converted it into <i>min L(x<sub>1</sub>, x<sub>2</sub>, …, x<sub>n</sub>, λ) = min {f(x<sub>1</sub>, x<sub>2</sub>, …, x<sub>n</sub>) – λh<sub>1</sub> (x<sub>1</sub>, x<sub>2</sub>, …, x<sub>n</sub>)}</i>. Then <i>L(x, λ)</i>, λ are known as Lagrangian function and Lagrangian function respectively.
This multiple choice question (MCQ) is related to the book/course
gs gs126 Neural Networks.
It can also be found in
gs gs126 Support Vector Machines - Optimality Conditions and Support Vectors - Quiz No.1.
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