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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.
上傳時間： 2013-12-16
上傳用戶：亞亞娟娟123
Polynomial fit functions === === === === regressionObject.cls contains a class that provides an easy way to add polynomial regression functionality to any application. If you just want linear regression or a very high degree, no matter: this class has good performance and scales seamlessly with the complexity of your problem.
標簽： regressionObject Polynomial functions contains
上傳時間： 2015-04-06
上傳用戶：rocwangdp
Support Vector Machines is a powerful methodology for solving problems in nonlinear classification and regression. It is a matlab version.
標簽： classification methodology nonlinear Machines
上傳時間： 2015-06-08
上傳用戶：bruce
The Bayesian Committee Machine (BCM) is an approximation method for large-scale Gaussian process regression. - The code is for Matlab Version 1.0, November 2005
標簽： approximation large-scale Committee Bayesian
上傳時間： 2015-09-14
上傳用戶：caiiicc
高斯過程是一種非參數化的學習方法，它可以很自然的用于regression，也可以用于classification。本程序用高斯過程實現分類！
上傳時間： 2015-10-22
上傳用戶：gxf2016
In this paper we propose to reduce the textural components by modelling the coefficients of a wedgelet based regression tree instead of the original pixel intensities
標簽： coefficients components modelling the
上傳時間： 2015-10-22
上傳用戶：gxmm
The subroutines glkern.f and lokern.f use an efficient and fast algorithm for automatically adaptive nonparametric regression estimation with a kernel method. Roughly speaking, the method performs a local averaging of the observations when estimating the regression function. Analogously, one can estimate derivatives of small order of the regression function.
標簽： automatically subroutines and algorithm
上傳時間： 2015-11-25
上傳用戶：luke5347
Support Vector Machine is small sample method based on statistic learning theory. It is a new method to deal with the highly nonlinear classification and regression problems .It can better deal with the small sample, nonlinear and
標簽： method statistic learning Support
上傳時間： 2014-12-02
上傳用戶：zukfu
PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis practice. For the latter part it is assumed (but not absolutely necessary) that the reader is already familiar with these methods. It also assumes you have had some preliminary experience with linear/matrix algebra.
標簽： Component Principal Analysis bilinear
上傳時間： 2016-02-07
上傳用戶：zuozuo1215
本人編寫的incremental 隨機神經元網絡算法，該算法最大的特點是可以保證approximation特性，而且速度快效果不錯，可以作為學術上的比較和分析。目前只適合benchmark的regression問題。 具體效果可參考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006.
標簽： incremental 編寫 神經元網絡 算法
上傳時間： 2016-09-18
上傳用戶：litianchu
