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局部线性回归方法及其稳健形式已经被看作一种有效的非参数光滑方法.与流行的核回归方法相比,它有诸多优点,诸如:较高的渐近效率和较强的适应设计能力.另外,局部线性回归能适应几乎所有的回归设计情形却不需要任何边界修正。,Local linear regression methods and their solid form has been seen as an effective non-parametric smoothing method. Contrary to popular kernel
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核函数是利用支持向量机解决不可分问题时引入的一种非线性变换的手段。基本思想是通过非线性变换，使样本变换之后的特征空间中变得线性可分。然后利用线性可分时构造最优超平面的方法，在特征空间中实现最优超平面的求解。-Kernel function is the use of support vector machine to resolve the issue can not be separated from the introduction of a nonlinear transform mean
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这个帖子中我想讨论的是移动窗口多项式最小二乘拟和平滑方法，粗糙惩罚方法，以及kernel平滑方法。-Posts in this discussion I think are moving window least squares polynomial fitting smoothing method, crude methods of punishment, as well as the kernel smoothing method.
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模糊核聚类算法的几篇论文及matlab源码，可以以练代学，更好掌握模糊聚类方法。-Fuzzy Kernel Clustering Algorithm matlab several papers and source code, can be practicing on behalf of science, to better grasp the fuzzy clustering method.
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kernel adatron, svm impelemtation using gradient ascent method, fast and accurate for solving SVM problem with two classes
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Kernel adatron, solving svm with gradient ascend method. fast and accurate.
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盲源分离FastICA、matalab程序，-FAST KERNEL ICA |
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Version 1.0- February 2007
Copyright 2007 Stefanie Jegelka, Hao Shen, Arthur Gretton
This package contains a Matlab implementation of the Fast Kernel ICA
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In kernel ridge regression we have seen the final solution was not sparse in the variables ® .
We will now formulate a regression method that is sparse, i.e. it has the concept of support
vectors that determine the solution.
The thing to not
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A method for classification of image using svm kernel
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核主成分分析方法，是主成分分析的一种改进算法，是一种非线性的特征提取方法。
-Kernel principal component analysis, is the principal component analysis of an improved algorithm, is a nonlinear feature extraction method.
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在ORL或Yale标准人脸数据库上完成模式识别任务。用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验.
-Or Yale in the ORL face database, complete the standard pattern recognition tasks. With the PCA and kernel-based PCA (KPCA) method to complete the reconstruction of face image and reco
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基于核函数回归方法的图像去噪，图像平滑。对于图像领域的研究者有很大作用-Kernel regression method based on image denoising, image smoothing. Researchers in the field for the image plays a significant role
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基于核方法的主成分分析matlab源代码，比较经典，推荐学习。-Method based on kernel principal component analysis matlab source code, more classic, recommended learning.
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利用MAT—LAB对实验数据进行了基于表面轮廓法的三维图像重构，观察不同的平滑领域参数以及轮廓提取阈值对三维重构效果的影响。-In this paper，taking advantage
of MATLAB we reconstruct experiment data into three dimension image in the way of feature-based method，
and observe the effect of different parameters，s
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把那个软件包解压缩，添加到matlab路径下，运行@kde\mex\makemex.m，然后就可以调用kde函数创建核密度估计类对象，调用类对象的各种“方法”实现核密度估计、画图等-Next, running @ kde \ mex \ makemex. then can be called kde function creates kernel density estimation class object, the call of the object of "method" realiz
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支持向量机及核函数的matlab算法集-Matlab method for kernel function of support vector machine (SVM) and set
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BP网络表达傅里叶核函数,此次实验采用了两种方法，第一方法是在matlab中实现BP算法，然后用实现的BP算法实现对傅里叶核函数的逼近，第二种方法是调用matlab中的工具箱函数实现傅里叶和函数的逼近。-BP Network expression Fourier kernel, the experiments using two methods, the first method is to achieve BP algorithm in matlab, then use the BP algo
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一种特征提取方法：结合主元分析(PCA)和核主元分析（KPCA）的前馈神经网络（FNN）(A feature extraction method: the feedforward neural network (FNN) combined with principal component analysis (PCA) and kernel principal component analysis (KPCA))
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利用粒子群优化算法对支持向量机中的核函数参数和惩罚参数进行优化是非常有效的手段，可以大大提高鲁棒性。实际过程中读者可通过下载我上传的代码，简单进行修改和阅读附件论文即可快速掌握相关方面的知识，快速使用这一方法。(Particle swarm optimization (PSO) is a very effective method to optimize the kernel function parameters and penalty parameters of SVM, which can
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