Auto Topic: penalize
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penalize
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textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... ach expert k such that ˆyk ̸= y, update wk ←βwk 6.Normalize the weights so that ∑k wk =1. Hereβ is a number, 0<β< 1, that tells how much to penalize an expert for each mistake. |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... ach expert k such that ˆyk ̸= y, update wk ←βwk 6.Normalize the weights so that ∑k wk =1. Hereβ is a number, 0<β< 1, that tells how much to penalize an expert for each mistake. 722 Chapter 19 Learning from Examples We measure the success of this algorithm in terms of regret, whic ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... is too expressive, that is, when it contains many hypotheses that fit the data set well. Bayesian and MAP learning methods use the prior to penalize complexity. Typically, more complex hypotheses have a lower prior probability—in part because there so many of them. On the other h ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... with a fully connected network, because adding more parents to a node cannot decrease the likelihood (Exercise 21. MLPA). We are forced to penalize model complexity in some way. The MAP (or MDL) approach simply subtracts a penalty from the likelihood of each structure (after par ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... he goal, knocking over lamps and tables along the way. In testing, we might notice this kind of behavior and modify the utility function to penalize such damage, but it is difficult for the designers and testers to anticipateall possible side effects ahead of time. One way to deal ... |