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Description: Returns weighted percentiles of a sample given the weight vector w
％ The idea is to give more emphasis in some examples of data as compared to
％ others by giving more weight. For example, we could give lower weights to
％ the outliers.
％ The motivation to write this function is to compute percentiles for Monte
％ Carlos simulations where some simulations are very bad (in terms of goodness
％ of fit between simulated and actual value) than the others and to give
％ the lower weights based on some goodness of fit criteria.-Returns weighted percentiles of a sample given the weight vector w The idea is to give more emphasis in some examples of data as compared to others by giving more weight. For example, we could give lower weights to the outliers. The motivation to write this function is to compute percentiles for Monte Carlos simulations where some simulations are very bad (in terms of goodness of fit between simulated and actual value) than the others and to give the lower weights based on some goodness of fit criteria .
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Author: Jack |
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Description: 一种基于局部密度比权重设置模型的加权支持向量回归模型来单步求解多分类问题：该方法先分别对类样本中每类样本利用局部密度比权重设置模型求出每个样本的权重隶属因子,然后运用加权lib支持向量回归算法对所有样本进行训练,获得回归分类器,希望对大家有用!-Based on local density than the right to re-set model of weighted support vector regression models to single-step to solve multi-classification problems: The method is first on the type of samples, respectively, for each type of samples the use of local density than the right to re-set the model to derive the right of each sample weight attached to factor, and then use lib weighted support vector regression algorithm for all samples for training, access to regression classifier, hope useful for all of us!
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Author: 郭大 |
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Description: 针对SVM法线特征筛选算法仅考虑法线对特征筛选的贡献,而忽略了特征分布对特征筛选的贡献的不足,在对SVM法线算法进行分析的基础上,基于特征在正、负例中出现概率的不同提出了加权SVM法线算法,该算法考虑到了法线和特征的分布.通过试验可以看出,在使用较小的特征空间时,与SVM法线算法和信息增益算法相比,加权SVM法线算法具有更好的特征筛选性能.-Normal feature selection for SVM algorithm only considered normal for the contribution of feature selection, to the neglect of the characteristics of the distribution of feature selection have contributed to the lack of normal SVM algorithm based on the analysis, based on the characteristics of the positive and negative cases emergence of a different probability-weighted normal SVM algorithm, which takes into account the distribution and characteristics of normal. through the test can be seen in the use of smaller feature space, the normal and the SVM algorithm and information gain algorithm, normal weighted SVM algorithm has better performance of feature selection.
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Author: 苏苏 |
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Description: LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、
易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、
n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）
等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM source. LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.
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Author: 刘铁军 |
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Description:
LIBSVM 是台湾大学林智仁 (Chih-Jen Lin) 博士等开发设计的一个操作简单、易于使用、快速有效的通用 SVM 软件包，可以解决分类问题（包括 C- SVC 、n - SVC ）、回归问题（包括 e - SVR 、 n - SVR ）以及分布估计（ one-class-SVM ）等问题，提供了线性、多项式、径向基和 S 形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.
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Author: 小潘 |
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Description: 本文通过对Bayes、KNN、SVM 应用于中文文本分类进行比较实验研究。
应用ICTCLAS 对中文文档进行分词，在大维数，多数据情况下应用TFIDF 进行
特征选择，并同时利用它实现了对特征项进行加权处理，使文本库中的每个文本
具有统一的、可处理的结构模型。然后通过三类分类算法实现了对权值数据进行
训练和分类。-Based on the Bayes, KNN, SVM applied to compare the Chinese text categorization Study. Application ICTCLAS word segmentation of Chinese document, in large dimension, multiple-data cases where application TFIDF feature selection, and also use it to realize the characteristics of weighted items, so that each text text library with a unified, capable of handling structural model. Three types of classification algorithm then weights the data for training and classification.
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Author: wulili |
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Description: 一种加权支持向量机的算法，主要描述一种加权支持相机的数学描述，参看此文可以更深入理解加权支持向量机-Fast Weighted SVM training Algorithm
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Author: 张超省 |
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Description: 针对神经网络的瓦斯预测模型存在的泛化性能差且存在易陷入局部最优的缺点，提出了
基于最小二乘支持向量机(LS-SVM)时间序列瓦斯预测方法．由于标准最小二乘支持向量机
(L孓SVM)要求样本误差分布服从高斯分布，且标准LS-SVM丧失鲁棒性与稀疏性等特点，提出
了基于加权LS-SVM的瓦斯时间序列预测的方法，从而提高了标准L孓SVM模型的鲁棒性．其
中时间序列的嵌入维数与延迟时间采用了微熵率最小原则进行选取，在此基础上给出了基于加
权L孓SVM实现多步时间序列预测的算法实现步骤．最后利用MATLAB 7．1对其进行仿真研
究，通过鹤壁十矿1个突出工作面的瓦斯涌出数据实例对模型进行了验证．结果表明，加权
SVM模型比标准的L§SVM明显提高了鲁棒性，可较好地实现时间序列数据的多步预测．-The neural network gas prediction model is poor in generalization performance and
easy in fafling into the local optimal value．In order to overcome these shortcomings，we pro—
pose the time series gas prediction method of least squares support vector machine(L§SVM)．
However，in the LS-SVM case，the sparseness and robustness may lose，and the estimation of
the support values iS optimal only in the case of a Gaussian distribution of the error variables．
So，this paper proposes the weighted L孓SVM tO overcome these tWO drawbacks．Meanwhile，
the optimal embedding dimension and delay time of time series are obtained by the smallest dif—
ferential entropy method．On this basis，multi-step time series prediction algorithm steps are
given based on the weighted LS-SVM．Finally，the data of gas outburst in working face of Hebi
lOth mine iS adopted to validate this model．The results show that the predict effect of shortterm
the face gas emission is better using the weighted LS-SVM model than using
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Author: wanggen |
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Description: 基于加权LS-SVM的非线性系统内模控制的仿真程序，由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同-Emulator mode control based on weighted LS-SVM nonlinear systems identification signal are random signal, not the value of the fixed signal, so the program each time you run the results are likely to differ
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Author: maple |
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Description: LS-SVM Leave-One-Out Cross-Validation Demo
G. C. Cawley, "Leave-one-out cross-validation based model selection criteria for weighted LS-SVMs", Proceedings of the International Joint Conference on Neural Networks (IJCNN-2006), pages 1661-1668, Vancouver, BC, Canada, July 16-21 2006. (pdf)theoval.cmp.uea.ac.uk/~gcc/matlab/
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Author: leozajung |
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Description: NWFE:Nonparametric Weighted Feature Extraction for Classification，线性分类方法，类似于改进了了的LDA，使用中，结果有时候比SVM等好-classification, NWFE:Nonparametric Weighted Feature Extraction for Classification
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Author: mcm |
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Description: 全局核（线性）与局部核（高斯）的加权组合，用于改进SVM的拟合和预测能力-The global kernel (linear) and local kernel (Gauss) weighted combination, to improve the SVM ability of fitting and prediction
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Author: 张青 |
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Description: 加权支持向量机的控制图模式识别方法，不平衡的分类异常控制模式与支持向量机的趋势
-A weighted support vector machine method for control chart pattern recognition imbalanced classification of abnormal control trend patterns with SVM
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Author: 马芮东 |
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Description: This a weighted svr in matlab -This is a weighted svr in matlab
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Author: Nabil |
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Description: 采用加权网络中节点强度和权重都是幂率分布的模型，包含特征值与特征向量的提取、训练样本以及最后的识别，本程序的性能已经超过其他算法，多抽样率信号处理，包括最小二乘法、SVM、神经网络、1_k近邻法,实现了对10个数字音的识别程。- Using weighted model nodes in the network strength and weight are power law distribution, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, This program has exceeded the performance of other algorithms, Multirate signal processing, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Realization of 10 digital audio recognition progra.
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Author: jmtugx |
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Description: 对信号进行频谱分析及滤波，计算加权加速度,包括最小二乘法、SVM、神经网络、1_k近邻法,关于神经网络控制，matlab开发工具箱中的支持向量机，LDPC码的完整的编译码。- The signal spectral analysis and filtering, Weighted acceleration, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, On neural network control, matlab development toolbox support vector machine, Complete codec LDPC code.
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Author: nvzayv |
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Description: 多目标跟踪的粒子滤波器，采用了小波去噪的思想，包括最小二乘法、SVM、神经网络、1_k近邻法,GPS和INS组合导航程序，部分实现了追踪测速迭代松弛算法，采用加权网络中节点强度和权重都是幂率分布的模型。- Multi-target tracking particle filter, Using wavelet denoising thought, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, GPS and INS navigation program, Partially achieved tracking speed iterative relaxation algorithm, Using weighted model nodes in the network strength and weight are power law distribution.
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Author: bftuar |
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Description: 仿真图是速度、距离、幅度三维图像，使用混沌与分形分析的例程，计算加权加速度,包括最小二乘法、SVM、神经网络、1_k近邻法,对信号进行频谱分析及滤波。- FIG simulation speed, distance, amplitude three-dimensional image, Use Chaos and fractal analysis routines, Weighted acceleration, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, The signal spectral analysis and filtering.
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Author: gszafb |
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Description: 包含特征值与特征向量的提取、训练样本以及最后的识别，包括最小二乘法、SVM、神经网络、1_k近邻法,验证可用，是学习PCA特征提取的很好的学习资料，针对EMD方法的不足,计算加权加速度,给出接收信号眼图及系统仿真误码率。- Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Verification is available, Is a good learning materials to learn PCA feature extraction, For lack of EMD, Weighted acceleration, The received signal is given eye and BER simulation systems.
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Author: vsfmxwsh |
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Description: 利用matlab GUI实现的串口编程例子，计算加权加速度,包括最小二乘法、SVM、神经网络、1_k近邻法,LDPC码的完整的编译码，GPS和INS组合导航程序，matlab小波分析程序，一种噪声辅助数据分析方法,模拟数据分析处理的过程。- Use serial programming examples matlab GUI implementation, Weighted acceleration, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Complete codec LDPC code, GPS and INS navigation program, matlab wavelet analysis program, A noise auxiliary data analysis method, Analog data analysis processing.
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Author: whavizczc |
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