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0下载：
SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regula
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3下载：
最小二乘支持向量机,用于多元非线性回归分析,非线性拟合与预测-Least squares support vector machine for multi-linear regression analysis, nonlinear fitting and prediction
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本软件是 windows系统平台下的支持向量机软件，包括了支持向量机的几种常用类型，可用于分类和回归-This software is under the windows system platform support vector machine software, including support vector machines for some commonly-used type, can be used for classification and regression
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1下载：
SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike reg
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实现多输出的支持向量机回归，不需要对每一个输出都进行函数回归-Multi-output support vector machine regression，Each output does not need to be a function of the regression
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10下载：
一种多输入多输出支持向量回归机源代码，克服了传统支持向量机单输出的缺点-A multi-input multi-output support vector regression machine source code, to overcome the traditional single-output SVM shortcomings
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0下载：
lssvm
最小二乘支持向量机,用于多元非线性回归分析,非线性拟合与预测-Least squares support vector machine for multi-linear regression analysis, nonlinear fitting and prediction
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LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Since version 2.8, it implements an SMO-ty
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libsvm-3.22.rar LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Since version 2.8, it impl
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0下载：
多输入多输出最小二乘支持向量机，多输入多输出最小二乘支持向量回归机，-lssvm，Multi-output least-squares support vector regression machines
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BSVM解决了支持向量机（SVM），用于解决大型分类和回归问题。 它包括以下方法
一个对一个使用约束约束公式的多类分类
通过解决单一优化问题（再次，有界公式）进行多类分类。 参见我们比较文件的第3节。
使用Crammer和Singer的配方进行多级分类。 参见我们的比较文章第4节。
使用约束约束公式的回归-BSVM solves support vector machines (SVM) for the solution of large classification and r
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1下载：
1-8遗传算法，9 多目标Pareto最优解搜索算法，10 基于多目标Pareto的二维背包搜索算法，11-12免疫算法，13-17粒子群算法，18鱼群算法，19-21模拟退火算法，22-24蚁群算法，25-27神经网络，28 支持向量机的分类，29 支持向量机的回归拟合，30 极限学习机的回归拟合及分类(1-8 genetic algorithm, 9 multi-objective Pareto optimal solution search algorithm, 10 multi-obje
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