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I read this introduction about AdaBoost (http://www.cs.man.ac.uk/~nikolaon/~nikolaon_files/Introduction_to_AdaBoost.pdf), and am curious why confidence for each model is defined as

$$\alpha_j=\frac{1}{2}\log\frac{1-\epsilon_j}{\epsilon_j}$$

(from page 48 of http://www.cs.man.ac.uk/~nikolaon/~nikolaon_files/Introduction_to_AdaBoost.pdf).

Could anyone provide any source for explaining this?

Thank you!

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