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svm-classification
- 此文件是利用支持向量机解决分类预测问题的一个简单的例子-This document is a simple example of using support vector machines to solve classification prediction problems
Review-on-the-theory-and-algorithm-
- 一篇讲解很好的支持向量机原理的资料，包括如何利用建立映射空间的最优分离超平面以及分类函数的建立-Information explaining a principle of good support vector machine, including how to establish an optimal separating hyperplane and the classification function to establish mapping space, etc.
haha
- 支持向量机(SVM)实现的分类算法源码，适合新手练习的svm分类器源代码，我觉得还是很有价值的。-Support vector machine (SVM) to achieve the classification algorithm source code, suitable for novice practice svm classifier source code, I think it is still very valuable.
55711236
- 用MATLAB编写的svm源程序,可以实现支持向量机,用于特征分类或提取,-MATLAB prepared by the SVM source program, can realize the support vector machine (SVM), used for extracting feature classification or,
patturnpatternclassification
- 支持向量机方法,用matlab实现,用于分类检测,模式识别,人脸检测等-Support vector machine (SVM) method, matlab, used for classification, pattern recognition, face detection, etc
mejhnq-detection-matlab
- 支持向量机方法,用matlab实现,用于分类检测,模式识别,人脸检测等-Support vector machine (SVM) method, matlab, used for classification, pattern recognition, face detection, etc
amspmbly
- 用MATLAB编写的svm源程序,可以实现支持向量机,用于特征分类或提取,-MATLAB prepared by the SVM source program, can realize the support vector machine (SVM), used for extracting feature classification or,
souvce-very
- 用matlab编写的用语分类的支持向量机 不错的源码 很好-Using matlab language classification support vector machine (SVM) good source is very good
dte
- 支持向量机方法,用matlab实现,用于分类检测,模式识别,人脸检测等-Support vector machine (SVM) method, matlab, used for classification, pattern recognition, face detection, etc
yonfqp83
- 用matlab编写的用语分类的支持向量机 不错的源码 很好-Using matlab language classification support vector machine (SVM) good source is very good
LIBSVMGUI20150708
- matlab中的GUI界面代码（可用于实现界面显示）和SVM支持向量机代码（最热分类方法）-Matlab GUI interface code (available for implementation interface display) and SVM support vector machine code (the hottest classification method)
SVM
- 通过支持向量机进行分类，实现了有监督的分类计算。-Through the support vector machine (SVM) classification, supervised classification calculation is realized.
mechine-learning
- 本书第一部分主要介绍机器学习基础，以及如何利用算法进行分类，并逐步介绍了多种经典的监督学习算法，如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树（CART）算法等。第三部分则重点介绍无监督学习及其一些主要算法：k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。 全书通过精心编排的实例，切入日常工作任务，摒弃学术化语言，利用高效的可复用Python代码来阐释如何处理统
libsvm_1.4.5-3.bin.windows
- 支持向量机分类算法，模式识别，多分类，语音识别。(Classification, pattern recognition)
SVM
- 使用支持向量机算法对二分类问题进行预测，实现大数据分析的目标。(Support vector machine algorithm is used to predict the two classification problem, and achieve the goal of large data analysis.)
mvrvm_matlab
- rvm回归预测 RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。(Rvm regression prediction)
hog_svm
- 利用HOG算子提取特征，利用支持向量机进行分类，得到了较好的图像分割效果(Using HOG operator to extract features, using support vector machine to classify, get a better image segmentation effect)
SVC
- 分类作为数据挖掘领域中一项非常重要的任务，它的目的是学会一个分类函数或分类模型(或者叫做分类器)，而支持向量机本身便是一种监督式学习的方法(Classification mining is a very important task in the field, the purpose of it is to learn a classification function or classification model (or called classifier), and support vec
svmcls
- 李荣陆老师做的文本分类器,特征选择方式包括全局和按类别选取，概率估算方法支持基于文档（布尔）统计和基于词频统计，支持三种特征加权方式，特征评估函数包括信息增益、互信息、期望交叉熵、X^2统计，文本证据权重，右半信息增益，分类方法包括支持向量机SVM和K近邻KNN，(text classifier that was written by Li Ronglu)
SVM
- 配置opencv库，SVM训练和分类，显示分类结果，和支持向量机。对于初学者了解SVM分类器由一定帮助(Configure the opencv library, SVM training and classification, display classification results, and support vector machines. For beginners understand the SVM classifier by some help)