文件名称:fpe
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This function calculates Akaike s final prediction error
％ estimate of the average generalization error.
％
％ [FPE,deff,varest,H] = fpe(NetDef,W1,W2,PHI,Y,trparms) produces the
％ final prediction error estimate (fpe), the effective number of
％ weights in the network if the network has been trained with
％ weight decay, an estimate of the noise variance, and the Gauss-Newton
％ Hessian.
％-This function calculates Akaike s final prediction error estimate of the average generalization error. [FPE, deff, varest, H] = fpe (NetDef, W1, W2, PHI, Y, trparms) produces the final prediction error estimate ( fpe), the effective number of weights in the network if the network has been trained with weight decay, an estimate of the noise variance, and the Gauss-Newton Hessian.
％ estimate of the average generalization error.
％
％ [FPE,deff,varest,H] = fpe(NetDef,W1,W2,PHI,Y,trparms) produces the
％ final prediction error estimate (fpe), the effective number of
％ weights in the network if the network has been trained with
％ weight decay, an estimate of the noise variance, and the Gauss-Newton
％ Hessian.
％-This function calculates Akaike s final prediction error estimate of the average generalization error. [FPE, deff, varest, H] = fpe (NetDef, W1, W2, PHI, Y, trparms) produces the final prediction error estimate ( fpe), the effective number of weights in the network if the network has been trained with weight decay, an estimate of the noise variance, and the Gauss-Newton Hessian.
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fpe.m
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