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. Platform: |
Size: 24576 |
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. Platform: |
Size: 518144 |
Author:小潘 |
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Description: 基于多元线性回归、偏最小二乘、神经网络、卡尔漫滤波、径向基网络、主成分分析等等的程序。可用于建模和预测。-Based on multiple linear regression, partial least squares, neural networks, Carl diffuse filtering, radial basis networks, and so on principal component analysis procedure. Can be used for modeling and prediction. Platform: |
Size: 24576 |
Author:yinjj |
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Description: A grid-connected wind-photovoltaic (PV) hybrid power system is proposed, and the steady-state model
analysis and the control strategy of the system are presented in this paper. The system consists of the PV
power, wind power, and an intelligent power controller. The General Regression Neural Network (GRNN)
algorithm applied to PV generation system which has non-linear characteristic and analyzed performance.
A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm
is designed to derive the turbine speed to extract maximum power the wind.-A grid-connected wind-photovoltaic (PV) hybrid power system is proposed, and the steady-state model
analysis and the control strategy of the system are presented in this paper. The system consists of the PV
power, wind power, and an intelligent power controller. The General Regression Neural Network (GRNN)
algorithm applied to PV generation system which has non-linear characteristic and analyzed performance.
A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm
is designed to derive the turbine speed to extract maximum power the wind. Platform: |
Size: 846848 |
Author:Rachid/s |
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Description: SVM Light工具箱 Matlab接口，已经编译好，可直接用(SVMlight, by Joachims, is one of the most widely used SVM classification and regression package. It has a fast optimization algorithm, can be applied to very large datasets, and has a very efficient implementation of the leave-one-out cross-validation. Distributed as C++ source and binaries for Linux, Windows, Cygwin, and Solaris. Kernels: polynomial, radial basis function, and neural (tanh).) Platform: |
Size: 66560 |
Author:ym89413
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Description: 支持向量机由Vapnik首先提出，像多层感知器网络和径向基函数网络一样，支持向量机可用于模式分类和非线性回归，该程序主要实现svm的分类和回归功能。(SVM was first proposed by Vapnik. Like multilayer sensor network and radial basis function network, SVM can be used for pattern classification and non-linear regression. The program mainly implements svm classification and regression functions.) Platform: |
Size: 17408 |
Author:wj2511
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Description: SURROGATES工具箱是一个多维函数逼近和优化方法的通用MATLAB库。当前版本包括以下功能：
实验设计：中心复合设计，全因子设计，拉丁超立方体设计，D-optimal和maxmin设计。
代理：克里金法，多项式响应面，径向基神经网络和支持向量回归。
错误和交叉验证的分析：留一法和k折交叉验证，以及经典的错误分析（确定系数，标准误差;均方根误差等;）。
基于代理的优化：高效的全局优化（EGO）算法。
其他能力：通过安全裕度进行全局敏感性分析和保守替代。(SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods. The current version includes the following capabilities:
Design of experiments: central composite design, full factorial design, Latin hypercube design, D-optimal and maxmin designs.
Surrogates: kriging, polynomial response surface, radial basis neural network, and support vector regression.
Analysis of error and cross validation: leave-one-out and k-fold cross-validation, and classical error analysis (coefficient of determination, standard error; root mean square error; and others).
Surrogate-based optimization: efficient global optimization (EGO) algorithm.
Other capabilities: global sensitivity analysis and conservative surrogates via safety margin.) Platform: |
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Author:pluto1888 |
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Search - Radial basis regression