Unformatted text preview: np ) ( A n , B n ) = (1 , 0) consider the following classiﬁcation scheme: for a new sample x new = ( x 1 , ..., x p ), choose h and calculate ˆ A ( x new ) = ∑ n i =1 K (  X ix new  /h ) A i ∑ n i =1 K (  X ix new  /h ) and ˆ B ( x new ) = ∑ n i =1 K (  X ix new  /h ) B i ∑ n i =1 K (  X ix new  /h ) Deﬁne the probability that x new ∈ A and B respectively as p A ( x new ) = exp( ˆ A ( x new )) exp( ˆ A ( x new )) + exp( ˆ B ( x new )) , p B ( x new ) = exp( ˆ B ( x new )) exp( ˆ A ( x new )) + exp( ˆ B ( x new )) We classify x new ∈ A if p A ( x new ) > p B ( x new ) , and x new ∈ B otherwise. Consider the banknotes data with ( training set and ( validation set , with h = 1 what is the classiﬁcation error? try diﬀerent h . (CODE) 1...
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 Fall '09
 XIAYingcun
 Statistics, Linear Regression, Regression Analysis, linear regression model

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