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LSSVMstudy
- 对学习最小二乘法的初学者有很大的帮助的一篇文章最小二乘支持向量机算法及应用研究-Least square method of learning is very useful to beginners in an article- least squares support vector machine algorithm and applied research
FaceDe
- 基于支持向量聚类的多聚焦图像融合算法. 从无监督机器学习角度提出了一种基于SVC(support vector clustering)的图像融合规则,解决了基于 SVM(support vector machine)的融合规则在处理多聚焦图像融合问题时所引起的区域混叠与非平滑过渡问题,进一步提高了融合图像的质量.-Based on support vector clustering algorithm for multi-focus image fusion. Never oversig
datamining
- 介绍了数据挖掘的各种方法（如支持向量机，神经网络，遗传算法）在地震预测中的应用-Introduced a variety of data mining methods (such as support vector machines, neural networks, genetic algorithms) in the earthquake prediction
svm-cailiao
- 支持向量机的原理、应用。支持向量机的算法、综述、核函数的定义等-Support vector machine principle, application. Support vector machine algorithm, summarized the definition of kernel function
CharlesLiSVR1.2
- 支持向量回归机工具箱。自编。带有GUI界面和使用教程。基于PCA降维和遗传算法寻优-Support vector regression toolbox. Self. With a GUI interface and tutorials. PCA dimensionality reduction based and genetic algorithm optimization
classificiation-algorithm-overview
- 机器学习领域经典分类算法综述，包括Decision Tree（ＩＤ３、C4.5(C5.0)、CART、PUBLIC、SLIQ和SPRINT算法），三种典型贝叶斯分类器（朴素贝叶斯算法、TAN算法、贝叶斯网络分类器），k-近邻 、 基于数据库技术的分类算法（ MIND算法、GAC-RDB算法），基于关联规则（CBA:Classification Based on Association Rule）的分类（Apriori算法），支持向量机分类，基于软计算的分类方法（粗糙集（rough set）、遗传
SVM-tutorial
- 最常见机器学习算法SVM的发展研究，从逻辑斯特研究到支持向量机-The most common SVM machine learning algorithm development research to logistic support vector machine
Based-on-the-pso-of-PSO
- 本文描述的是用粒子群优化算法下的支持向量机的研究，详细概述了其优化参数-This article describes the algorithm under the support vector machine optimized by particle swarm optimization parameters detailed overview of its
PSO-optimization-of-SVM
- 这篇文章主要描述了基于粒子群算法下的支持向量积的研究-This article describes a study based on support vector particle swarm under integrable