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基于matlab的SVM三分类算法
- SVM的多分类问题,在matlab平台下的源代码分析。
根据鸢尾花多组数据先训练网络再对样本进行测试
- 基于BP神经网络,根据鸢尾花多组数据先训练网络再对样本进行测试,给出分类结果,Based on BP neural network, in accordance with multiple sets of data iris network before training again for testing classification results are given
OSU_SVM3.00
- matlab支持向量机用于多类模式的分类,较全面,可以迅速解决问题,值得下载!-matlab support vector machine model for multi-category classification, a more comprehensive, you can quickly solve the problem, it is worth to download!
oao
- 多分类问题的支持向量机源程序一对一方法 绝对可以运行-Multi-class SVM using One-Against-One decompositionoao
mill
- 包含了很多分类算法,有SVM,knn,决策树等,还有文档说明-Contains a lot of classification algorithms, there is SVM, knn, decision tree and so on, have documented
multiboost-0.61.src.tar
- Adaboost实现,主要用于机器学习的多分类器聚合, 最终形成分类效果逐渐增强的分类器-Adaboost implementation, is mainly used for machine learning, multiple classifier aggregation, the final shape classification results show a gradual increase of the classifier
program
- 模式识别中分类程序,实现了很多分类算法,有兴趣的朋友可以研究下-Pattern recognition, many classification procedures classification algorithm, interested friends may study
SVM
- 这个是svm的一遍小论文 比较好 基于模糊核聚类的svm多类分类方法-svm
libsvm实现文本分类源程序
- libsvm实现文本分类源序,其中: 1.0Beta ,是打包好的可执行的jar文件,运行前需要配置一下,具体看目录下的README.TXT; 程序工程,是源代码,不过并不是和1.0Beta里面的完全一致; 实验样例,用来进行试运行的文本文件; 语料库,包含了3000多份文档的语料库,用"抽取"将在单个文档中的多个类型的文本提取到ouput目录下
BP
- BP神经网络实现多分类,代码包括六分类以及二分类(The BP neural network implements multiple classifications. The code includes six categories and two categories.)
perception
- 多分类的感知器算法,包括Ho_Kashyap的mse实现(Multiple classification of perceptron algorithms, including the MSE implementation of Ho_Kashyap)
Multi-Class BCI
- 全面总结多分类BCI的实验范式,具有很好的指导作用(A comprehensive summary of the experimental paradigm of multiclass BCI has a good guiding role.)
wine
- SVM多分类算法,基于svmlib适合初学者学习(SVM multi classification algorithm, based on svmlib suitable for beginners to learn)
Sample4
- 支持svm多分类,运算时间较长,支持svm多分类的matlab代码,精度不高。(Support svm multi-classification)
libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]
- 一般的支持向量机只支持二分类,使用libsvm可以实现多分类,原理也是基于二分类,然后在使用投票机制,经测验,libsvm的分类精度可达85%以上(Multi class supported by libsvm,after testing, the classification accuracy can reach 85%.)
多条件分类筛选查询代码
- jQuery多条件分类筛选查询代码是一款支持多选条件,更多分类,关键字查询筛选代码。(JQuery multi-condition classification and filtering query code is a kind of code that supports multiple selection conditions, more classification, keyword query and filtering.)
19107matlab自编svm
- 利用原算法adaboost弱学习器基于决策树桩的方法对样本数据进行多分类(Multi-classification of sample data based on decision tree stump using AdaBoost weak learner)
mtsvm
- 多分类孪生支持向量机,主体是-1 1的2分类孪生支持向量机,采用onevsone改编成多分类的孪生支持向量机(multi classification twin support vector machine, kernel code is binary-classification twin support vector machine ,constructed it as a multi classification twin support vector machine by using O
svm多分类
- 用于svm多分类,值得学习,可以尝试运行,修改后使用。
逻辑回归
- 根据标签,完成SVM下的多分类数据识别,数据可以是字符或者信号,可以达到较高的识别精度(The multi-classification data recognition under SVM was completed)