登录
首页 » matlab » ELM

ELM

于 2018-03-14 发布 文件大小:3947KB
0 358
下载积分: 1 下载次数: 11
我要下载

代码说明：

  一种神经网络算法：极限学习机（ELM)，包括分类和回归，仿真验证无误，适合初学者练习(A data mining algorithm: limit learning machine (ELM), including classification and regression, simulation verification is unmistakable, suitable for beginners to practice)

文件列表：

ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes)\BP_diabetes.m, 2265 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes)\BP_sinc.asv, 2298 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes)\diabetes2.dt, 46403 , 2004-03-18
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes)\diabetes2_data.m, 1161 , 2004-04-17
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes)\diabetes_test, 19200 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes)\diabetes_train, 57600 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\diabetes2.dt, 46403 , 2004-03-18
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\diabetes2_data.m, 1161 , 2004-04-17
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\diabetes_test, 19200 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\diabetes_train, 57600 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\ELM.asv, 9389 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\ELM.m, 9390 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes)\ELM_diabetes.m, 874 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM.m, 9385 , 2013-08-31
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\elm_predict.m, 3763 , 2004-05-10
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\elm_train.m, 5645 , 2004-05-10
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes)\diabetes2.dt, 46403 , 2004-03-18
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes)\diabetes2_data.m, 1161 , 2004-04-17
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes)\diabetes_test, 19200 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes)\diabetes_train, 57600 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes)\SVM_diabetes.asv, 2224 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes)\SVM_diabetes.m, 2250 , 2013-10-03
ELM\ELMѧϰ\Basic ELM(for ELM with random hidden nodes)\elm.pdf, 460493 , 2013-10-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\BP(SINC)\BP_sinc.m, 1481 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\BP(SINC)\sinc.m, 706 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\BP(SINC)\sinc_mean.asv, 1463 , 2013-09-05
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\BP(SINC)\sinc_test, 687 , 2013-10-21
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\BP(SINC)\sinc_train, 2280 , 2013-10-21
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC)\ELM.m, 7862 , 2013-09-06
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC)\ELM_sinc.m, 780 , 2013-10-05
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC)\sinc.m, 706 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC)\sinc_mean.asv, 786 , 2013-09-05
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC)\sinc_test, 682 , 2014-05-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC)\sinc_train, 2290 , 2014-05-03
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM.m, 9385 , 2013-08-31
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\elm_predict.m, 3763 , 2004-05-10
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\elm_train.m, 5645 , 2004-05-10
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC)\sinc.m, 706 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC)\sinc_mean.asv, 1463 , 2013-09-05
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC)\sinc_test, 681 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC)\sinc_train, 2302 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC)\SVR_sinc.asv, 2185 , 2013-09-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC)\SVR_sinc.m, 2186 , 2013-09-14
ELM\ELMѧϰ\B_ELM\B-ELM.zip, 1341073 , 2013-10-05
ELM\ELMѧϰ\C_ELM\Compelx-ELM.zip, 377581 , 2013-10-05
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes)\diabetes2.dt, 46403 , 2004-03-18
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes)\diabetes2_data.m, 1161 , 2004-04-17
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes)\diabetes_test, 19200 , 2013-10-05
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes)\diabetes_train, 57600 , 2013-10-05
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes)\elm_kernel.m, 7861 , 2013-10-05
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes)\ELM_kernel_diabetes.m, 889 , 2013-10-05
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC)\elm_kernel.m, 7861 , 2013-10-05
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC)\ELM_kernel_sinc.m, 795 , 2013-10-05
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC)\sinc.m, 706 , 2013-09-14
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC)\sinc_mean.asv, 786 , 2013-09-05
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC)\sinc_test, 688 , 2013-10-05
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC)\sinc_train, 2287 , 2013-10-05
ELM\ELMѧϰ\OS_ELM\OS-ELM\HardlimActFun.m, 209 , 2006-06-06
ELM\ELMѧϰ\OS_ELM\OS-ELM\OSELM.m, 7690 , 2006-06-06
ELM\ELMѧϰ\OS_ELM\OS-ELM\OSELM_VARY.m, 7778 , 2006-06-06
ELM\ELMѧϰ\OS_ELM\OS-ELM\RBFun.m, 287 , 2006-06-06
ELM\ELMѧϰ\OS_ELM\OS-ELM\SigActFun.m, 211 , 2006-06-06
ELM\ELMѧϰ\OS_ELM\OS-ELM\SinActFun.m, 199 , 2006-06-06
ELM\ELMѧϰ\OS_ELM\oselm.pdf, 666139 , 2013-10-16
ELM\ELMѧϰ\SaDE_ELM\SaDE-ELM.rar, 4877 , 2013-10-05
ELM\ELMѧϰ\Weighted_ELM\Weighted-ELM.zip, 6993 , 2013-10-05
ELM\ELM学习\测试比较图.doc, 167936 , 2013-10-05
ELM\分类\ELMfenglei.m, 1741 , 2013-08-26
ELM\分类\elmpredict.m, 1454 , 2010-11-07
ELM\分类\elmtrain.m, 1752 , 2010-11-07
ELM\分类\iris.mat, 1059 , 2009-11-14
ELM\回归\chejing.mat, 213954 , 2014-07-04
ELM\回归\elm\chejing.mat, 213954 , 2014-07-04
ELM\回归\elm\ELM.m, 2298 , 2014-07-04
ELM\回归\elm\elmpredict.m, 1454 , 2010-11-07
ELM\回归\elm\elmtrain.m, 1752 , 2010-11-07
ELM\回归\ELMhuigui.m, 3444 , 2014-07-04
ELM\回归\elmpredict.m, 1454 , 2010-11-07
ELM\回归\elmtrain.m, 1752 , 2010-11-07
ELM\回归\main.asv, 3194 , 2013-08-26
ELM\回归\psoelm\chejing.mat, 213954 , 2014-07-04
ELM\回归\psoelm\elmpredict.m, 1454 , 2010-11-07
ELM\回归\psoelm\elmtrain.m, 3605 , 2014-07-04
ELM\回归\psoelm\fun.m, 1181 , 2014-07-04
ELM\回归\psoelm\PSOELM.m, 2391 , 2014-07-04
ELM\回归\psoelm.zip, 428805 , 2014-07-04
ELM\回归\spectra_data.mat, 171497 , 2010-10-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\BP(diabetes), 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\ELM(diabetes), 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类\SVM(diabetes), 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\BP(SINC), 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\ELM(SINC), 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归\SVR(SINC), 0 , 2018-03-14
ELM\ELM学习\ELM_kernel\diabetes分类\ELM_kernel(diabetes), 0 , 2018-03-14
ELM\ELM学习\ELM_kernel\sinc回归\ELM_kernel(SINC), 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\diabetes分类, 0 , 2018-03-14
ELM\ELM学习\Basic ELM(for ELM with random hidden nodes)\sinc回归, 0 , 2018-03-14
ELM\ELM学习\ELM_kernel\diabetes分类, 0 , 2018-03-14
ELM\ELM学习\ELM_kernel\sinc回归, 0 , 2018-03-14
ELM\ELMѧϰ\OS_ELM\OS-ELM, 0 , 2018-03-14

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • PCA
    说明：  一个用python实现的PCA算法，并且给了简易素材(A PCA algorithm implemented in python, and gave a simple material)
    2020-08-23 14:38:17下载
    积分：1
  • emd program-matlab
    说明：  EMD经验模态分解算法程序，适合非线性，非平稳时间序列的处理(EMD empirical mode decomposition algorithm program)
    2019-01-14 20:43:57下载
    积分：1
  • AP聚类
    说明：  实现了无监督AP聚类 其优势在于不用知道聚类个数(The advantage of unsupervised AP clustering is that the number of clusters is not known)
    2020-08-13 18:05:48下载
    积分：1
  • qb神经网络
    从数据库获取车辆在一段时间内的所有行驶记录的相关数据，确定所需数据为GPS经纬度坐标和驾驶时长等，QB模型采用MDF的思想,其基本思想为:通过平均直接翻转距离函数定义两条轨迹之间的距离，两条轨迹需要具有相同的经纬度点数，具有相同点数的轨迹最大的优点是对轨迹距离成对计算，且相同轨迹之间具有更高的分辨率，对于轨迹聚类的结果有一定的优化。(Retrieved from the database cars all over a period of time, record the related data, determine the required data for the GPS latitude and longitude coordinates, and the driving time, QB model by adopting the idea of MDF, its basic idea is: flip directly by the average distance function definition of the distance between two trajectories, two tracks will have the same latitude and longitude points, and has the biggest advantages of the same points of trajectory track distance calculation in pairs, and has higher resolution, between the same trajectory for trajectory clustering results have certain optimization.)
    2020-06-23 08:00:01下载
    积分：1
  • HMM-homework
    说明：  隐马尔科夫实现，包含forward-hmm, Viterbi-hmm, Baum-Welch-hmm(Hidden Markov implementation, including forward-hmm, Viterbi-hmm, Baum-Welch-hmm)
    2019-04-26 17:02:43下载
    积分：1
  • 从零开始学Python网络爬虫源代码+教学PPT
    《从零开始学爬虫》的配套资料（PPT和源码）("Learning Reptiles from Zero" (PPT and Source))
    2019-03-18 22:06:06下载
    积分：1
  • OPTICS
    此为利用optics聚类方法剔除风电异常数据后，采用极限学习机验证的代码(optics data mining)
    2017-03-22 19:29:22下载
    积分：1
  • BIC确定GMM聚类簇数
    通过贝叶斯信息准则确定高斯混合聚类方法的聚类簇数(Determining the Cluster Number of GMM Clusters by BIC)
    2021-03-26 19:19:13下载
    积分：1
  • kasterenDataset
    主要针对行为识别，常用数据处理方法及分类，可视化 包含数据集(Mainly for behavior recognition, commonly used data processing methods and classification, visualization Contain data sets)
    2021-03-30 10:29:10下载
    积分：1
  • 8641704
    插值抽取的内容,数字变频用, 分享了,请高手完善指教,()
    2018-05-25 06:35:56下载
    积分：1
  • 696516资源总数
  • 106554会员总数
  • 12今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！