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generalization

  • This function calculates Akaike s final prediction error % estimate of the average generalization e

    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. %

    標簽: generalization calculates prediction function

    上傳時間: 2014-12-03

    上傳用戶:maizezhen

  • This function calculates Akaike s final prediction error % estimate of the average generalization e

    This function calculates Akaike s final prediction error % estimate of the average generalization error for network % models generated by NNARX, NNOE, NNARMAX1+2, or their recursive % counterparts. % % [FPE,deff,varest,H] = nnfpe(method,NetDef,W1,W2,U,Y,NN,trparms,skip,Chat) % produces the final prediction error estimate (fpe), the effective number % of weights in the network if it has been trained with weight decay, % an estimate of the noise variance, and the Gauss-Newton Hessian. %

    標簽: generalization calculates prediction function

    上傳時間: 2016-12-27

    上傳用戶:腳趾頭

  • generalization of a Simple Genetic Algorithm (GA)

    generalization of a Simple Genetic Algorithm (GA)

    標簽: generalization Algorithm Genetic Simple

    上傳時間: 2017-05-02

    上傳用戶:BOBOniu

  • 最新的支持向量機工具箱

    最新的支持向量機工具箱,有了它會很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999.

    標簽: 支持向量機 工具箱

    上傳時間: 2013-12-16

    上傳用戶:亞亞娟娟123

  • This standard describes a keyed-hash message authentication code (HMAC), a mechanism for message au

    This standard describes a keyed-hash message authentication code (HMAC), a mechanism for message authentication using cryptographic hash functions. HMAC can be used with any iterative Approved cryptographic hash function, in combination with a shared secret key. The cryptographic strength of HMAC depends on the properties of the underlying hash function. The HMAC specification in this standard is a generalization of Internet RFC 2104, HMAC, Keyed-Hashing for Message Authentication, and ANSI X9.71, Keyed Hash Message Authentication Code.

    標簽: message authentication keyed-hash describes

    上傳時間: 2014-01-07

    上傳用戶:鳳臨西北

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