首页 开发技术 其它     /    粗糙集约简算法的实现(代码)

粗糙集约简算法的实现(代码)

上传者: zwq1987 | 上传时间:2022/9/7 4:18:18 | 文件大小:38KB | 文件类型:zip
粗糙集约简算法的实现(代码)
粗糙集约简算法次要是从别人那边搞来的,为了方便大家,作为研究中不停使用的粗糙集方面想必大家也是很头疼代码问题

文件下载

资源详情

[{"title":"(35个子文件38KB)粗糙集约简算法的实现(代码)","children":[{"title":"Matlabcodeofroughset","children":[{"title":"Neighborhoodroughsetbasedfeatureevaluationandreduction","children":[{"title":"clsf_dpd_fast_3.m <span style='color:#111;'>1.49KB</span>","children":null,"spread":false},{"title":"clsf_dpd.m <span style='color:#111;'>1.42KB</span>","children":null,"spread":false},{"title":"NRS_FW_FS.m <span style='color:#111;'>3.25KB</span>","children":null,"spread":false},{"title":"clsf_dpd_fast2.m <span style='color:#111;'>1.79KB</span>","children":null,"spread":false},{"title":"clsf_dpd_fast.m <span style='color:#111;'>1.55KB</span>","children":null,"spread":false}],"spread":true},{"title":"RankingheterogeneousfeatureswithmRMRandmutualinformation","children":[{"title":"MI_mRMR.m <span style='color:#111;'>4.58KB</span>","children":null,"spread":false}],"spread":true},{"title":"datareductionwithfuzzyroughsetsorfuzzymutualinformation","children":[{"title":"fs_entropy.asv <span style='color:#111;'>2.42KB</span>","children":null,"spread":false},{"title":"fs_con_N.m <span style='color:#111;'>2.38KB</span>","children":null,"spread":false},{"title":"demo.m <span style='color:#111;'>495B</span>","children":null,"spread":false},{"title":"kersim.m <span style='color:#111;'>230B</span>","children":null,"spread":false},{"title":"wine.mat <span style='color:#111;'>9.33KB</span>","children":null,"spread":false},{"title":"fs_neighbor.m <span style='color:#111;'>2.66KB</span>","children":null,"spread":false},{"title":"entropy.m <span style='color:#111;'>164B</span>","children":null,"spread":false},{"title":"entropy_interval.m <span style='color:#111;'>682B</span>","children":null,"spread":false},{"title":"kersim_crisp.m <span style='color:#111;'>94B</span>","children":null,"spread":false},{"title":"fs_entropy.m <span style='color:#111;'>2.81KB</span>","children":null,"spread":false},{"title":"fs_neighbor.asv <span style='color:#111;'>2.63KB</span>","children":null,"spread":false}],"spread":false},{"title":"kernelizedfuzzyroughsetbasedfeatureevaluationselection","children":[{"title":"dependency_theta_gs.m <span style='color:#111;'>1.18KB</span>","children":null,"spread":false},{"title":"FS_GKFS.m <span style='color:#111;'>2.50KB</span>","children":null,"spread":false},{"title":"dependency_s_gs.m <span style='color:#111;'>1.16KB</span>","children":null,"spread":false},{"title":"certainty_theta_gs.m <span style='color:#111;'>1.29KB</span>","children":null,"spread":false},{"title":"certainty_s_gs.m <span style='color:#111;'>1.23KB</span>","children":null,"spread":false}],"spread":true},{"title":"neighborhoodclassifier","children":[{"title":"neighborhoodclassifier","children":[{"title":"KNN.m <span style='color:#111;'>1.74KB</span>","children":null,"spread":false},{"title":"NEC.m <span style='color:#111;'>1.75KB</span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"fuzzypreferenceroughsetbasedfeatureevaluationandselection","children":[{"title":"FS_PL_FRS.m <span style='color:#111;'>2.12KB</span>","children":null,"spread":false},{"title":"FUC.m <span style='color:#111;'>1.24KB</span>","children":null,"spread":false},{"title":"GC.m <span style='color:#111;'>1.98KB</span>","children":null,"spread":false},{"title":"LC.m <span style='color:#111;'>1.14KB</span>","children":null,"spread":false},{"title":"FGC.m <span style='color:#111;'>2.14KB</span>","children":null,"spread":false},{"title":"FS_PL_RS.m <span style='color:#111;'>1.91KB</span>","children":null,"spread":false},{"title":"UC.m <span style='color:#111;'>1.17KB</span>","children":null,"spread":false},{"title":"FLC.m <span style='color:#111;'>1.23KB</span>","children":null,"spread":false}],"spread":true},{"title":"KNNclassifier","children":[{"title":"KNN.m <span style='color:#111;'>1.34KB</span>","children":null,"spread":false}],"spread":true},{"title":"neighborhoodmutualinformationbasedfeatureevaluationandselection","children":[{"title":"FS_FW_NE.m <span style='color:#111;'>2.17KB</span>","children":null,"spread":false},{"title":"NMI.m <span style='color:#111;'>649B</span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]

评论信息

  • am88888888am:
    下载看了一下,共有8个程序。是关于模糊粗糙集的,可以学习一下2021-06-10
  • am88888888am:
    下载看了一下,共有8个程序。是关于模糊粗糙集的,可以学习一下2021-06-10
  • weixin_39814560:
    很多种粗糙集代码,但是还是有点看不懂2019-10-27
  • zhouhanhaha:
    很多种粗糙集代码,但是还是有点看不懂2019-10-27
  • jnhj3032:
    下载看了一下,共有8个程序。是关于模糊粗糙集的,可以学习一下。2014-08-04
  • jnhj3032:
    下载看了一下,共有8个程序。是关于模糊粗糙集的,可以学习一下。2014-08-04
  • cluby1985:
    是MATLAB的,本想下载C语言的2013-12-04
  • cluby1985:
    是MATLAB的,本想下载C语言的2013-12-04
  • yxyyxy8868:
    共有8个matlab代码,与主题相符。算法跑的起来,代码也写得比较工整,有注释很值得参考。2013-06-04
  • 醉梦逸:
    共有8个matlab代码,与主题相符。算法跑的起来,代码也写得比较工整,有注释很值得参考。2013-06-04

免责申明

【好快吧下载】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【好快吧下载】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【好快吧下载】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,8686821#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明