搜索资源列表
sinc_train
- it is a elm dataset. it work we-it is a elm dataset. it work well
lsvm-and-knn-elm
- lsvm and knn elm For training: elm_traing(TrainingData_File, Elm_Type, NumberofHiddenNeurons, ActivationFunction) OR: [TrainingTime, TrainingAccuracy] = elm_train(TrainingData_File, Elm_Type, NumberofHiddenNeurons, ActivationFunction) For te
ELM
- MATLAB实现ELM算法,并附带UCI经典数据。-MATLAB realization ELM algorithm, along with the classic UCI data.
ELM
- 极端学习机分类回归的源代码,可实现预测功能-ELM classification and regression source code, enabling prediction function
67506268SS-US-ELM
- SS-ELM和US-ELM的程序代码,可以运行-SS-ELM and US-ELM program code, you can run
4-elm-examples
- 4个 elm例子,供大家学习极限学习机,请批评指正-four elm examples for every one
103796
- ELM for large scale datasets
B-ELM
- bidirectional elm matlab code
H-ELM
- Extreme Learning Machine for Multilayer Perceptron
B2DPCA和ELM人脸识别算法研究_李定珍
- 提出一种新型、高效的基于 B2DPCA(双向二维主成分分析)和 ELM(极端学习机)的人脸识别算法, 该算法是根据曲波变换分解人脸图像和一种改进的降维技术,通 过 B2DPCA 生成识别特征集来训练和测试 ELM 分类器,提高识别精度。通过大量实验,并把实验结果与现存技术进行比较,结果表明 B2DPCA+ELM 算法有效地提高了识别准确率,并降低了对原型数量的依赖。将来有望能把局部特征和基于曲波分解的全 局信息结合起来应用到识别精度和分类速度上。(a new human recognit
basic-elm
- 极限学习机的基本实现,是黄广斌教授最早提出的最初始的代码(the basic elm is the professor Huang proposed the first time)
ELM+JAVA
- OS-ELM识别分类代码,是一种很好的识别方法(os-elmNumberofHiddenNeurons - Number of hidden neurons assigned to the ELM % ActivationFunction - Type of activ)
ELM
- 极限学习机,核心机代码,来自于新加坡NTU黄教授网站(ELM,from the website of prof.huang)
H-ELM算法
- H——ELM算法由黄老师提供,在这里提供更大家分享在这个资源。希望大家把其改进,一起分享
elm
- ELM(极限学习机)对序列进行预测,里面含有测试数据,可以运行,欢迎下载!(ELM (extreme learning machine) to predict the sequence, which contains test data, can run, welcome to download!)
ELM
- 采用python语言实现极限学习机算法,数据三分类,加入数据可以跑通(Using python language to achieve extreme learning machine algorithm, data three classification, join data can run through)
elm329-bt mini
- Circuit elm 329 end source programmes.
ELM分类
- 利用极限学习机elm来进行分类,你值得拥有,这个程序是可以实现的,有问题,一起讨论。(Use extreme learning machine elm to classify, you deserve it, thank you for this platform, thank you.)
ELM
- 极限学习机(ELM算法)初级版本,包括训练和测试两个版本,数据:http://benchmark.ini.rub.de/?section=gtsrb&subsection=news(Extreme learning machine (ELM algorithm) preliminary version)
免疫+ELM 回归
- 用免疫算法优化ELM的输入层到隐藏层的权值与阈值参数,以此来提高ELM的预测精度。(Optimizing ELM parameters with immune algorithms)