k-means聚类算法及matlab代码--:--

上传者: 38742927 | 上传时间: 2022-05-22 16:35:18 | 文件大小: 523KB | 文件类型: ZIP
k-means聚类算法及matlab代码 机器学习与数据挖掘实验 . 目录 实验内容 小组成员 队长:张奥翔 队员:何锦辉、王浩辉、吴振廷 仓库文件内容说明 文件/目录 说明 实验一 多源数据集成、清洗和统计 实验二 数据统计和可视化数据统计和可视化 实验三 k-means聚类算法 实验四 逻辑回归二分类 实验一 多源数据集成、清洗和统计 题目 : ​ 广州大学某班有同学100人,现要从两个数据源汇总学生数据。第一个数据源在数据库中,第二个数据源在txt文件中,两个数据源课程存在缺失 、冗余和不一致性,请用C/C++/Java程序实现对两个数据源的一致性合并以及每个学生样本的数值量化。 0、两个数据源合并后读入内存,并统计: 1、学生中家乡在Beijing的所有课程的平均成绩: 2、学生家乡在广州,课程1在80分以上,且课程9在9分以上的男同学的数量: 3、比较广州和上海两地女生的平均体能测试成绩,哪个地区的更强些? 4、学习成绩和体能测试成绩,两者的相关性是多少?(九门课的成绩分别与体能成绩计算相关性) (1) (2) 实验二 数据统计和可视化 题目 : 基于实验一中清洗后的数据练

文件下载

资源详情

[{"title":"( 46 个子文件 523KB ) k-means聚类算法及matlab代码--:--","children":[{"title":"--main","children":[{"title":"exp2","children":[{"title":"第一问.png <span style='color:#111;'> 31.96KB </span>","children":null,"spread":false},{"title":"第二问.png <span style='color:#111;'> 21.51KB </span>","children":null,"spread":false},{"title":"exp2.py <span style='color:#111;'> 2.81KB </span>","children":null,"spread":false},{"title":"合并数据.csv <span style='color:#111;'> 8.72KB </span>","children":null,"spread":false},{"title":"第三问correlation_matrix.txt <span style='color:#111;'> 71.58KB </span>","children":null,"spread":false},{"title":"第四问.png <span style='color:#111;'> 159.75KB </span>","children":null,"spread":false},{"title":"第五问最近样本.txt <span style='color:#111;'> 2.28KB </span>","children":null,"spread":false}],"spread":true},{"title":"exp1","children":[{"title":"第一问.png <span style='color:#111;'> 11.71KB </span>","children":null,"spread":false},{"title":"第三问.png <span style='color:#111;'> 3.24KB </span>","children":null,"spread":false},{"title":"第二问.png <span style='color:#111;'> 2.35KB </span>","children":null,"spread":false},{"title":"合并数据.csv <span style='color:#111;'> 8.72KB </span>","children":null,"spread":false},{"title":"第四问(2).png <span style='color:#111;'> 31.26KB </span>","children":null,"spread":false},{"title":"第四问(1).png <span style='color:#111;'> 17.05KB </span>","children":null,"spread":false},{"title":"exp1.py <span style='color:#111;'> 4.00KB </span>","children":null,"spread":false}],"spread":true},{"title":"exp4","children":[{"title":"第一问.png <span style='color:#111;'> 27.67KB </span>","children":null,"spread":false},{"title":"第三问.png <span style='color:#111;'> 27.24KB </span>","children":null,"spread":false},{"title":"第二问(1).png <span style='color:#111;'> 21.45KB </span>","children":null,"spread":false},{"title":"exp4.py <span style='color:#111;'> 2.71KB </span>","children":null,"spread":false},{"title":"第二问(2).png <span style='color:#111;'> 24.66KB </span>","children":null,"spread":false}],"spread":true},{"title":"exp3","children":[{"title":"yangli.txt <span style='color:#111;'> 218B </span>","children":null,"spread":false},{"title":"3cen=","children":[{"title":"c3exm2.txt <span style='color:#111;'> 119B </span>","children":null,"spread":false},{"title":"聚类3结果可视化散点图.png <span style='color:#111;'> 21.10KB </span>","children":null,"spread":false},{"title":"聚类3结果.png <span style='color:#111;'> 17.95KB </span>","children":null,"spread":false},{"title":"c3exm3.txt <span style='color:#111;'> 32B </span>","children":null,"spread":false},{"title":"c3exm1.txt <span style='color:#111;'> 93B </span>","children":null,"spread":false}],"spread":true},{"title":"4cen","children":[{"title":"聚类4结果.png <span style='color:#111;'> 21.21KB </span>","children":null,"spread":false},{"title":"c4exm1.txt <span style='color:#111;'> 31B </span>","children":null,"spread":false},{"title":"聚类4结果可视化散点图.png <span style='color:#111;'> 21.04KB </span>","children":null,"spread":false},{"title":"c4exm3.txt <span style='color:#111;'> 119B </span>","children":null,"spread":false},{"title":"c4exm4.txt <span style='color:#111;'> 9B </span>","children":null,"spread":false},{"title":"c4exm2.txt <span style='color:#111;'> 90B </span>","children":null,"spread":false}],"spread":true},{"title":"kmeans.cpp <span style='color:#111;'> 5.04KB </span>","children":null,"spread":false},{"title":"5cen","children":[{"title":"c5exm1.txt <span style='color:#111;'> 43B </span>","children":null,"spread":false},{"title":"c5exm4.txt <span style='color:#111;'> 8B </span>","children":null,"spread":false},{"title":"c5exm5.txt <span style='color:#111;'> 112B </span>","children":null,"spread":false},{"title":"c5exm2.txt <span style='color:#111;'> 9B </span>","children":null,"spread":false},{"title":"聚类5结果可视化散点图.png <span style='color:#111;'> 21.44KB </span>","children":null,"spread":false},{"title":"c5exm3.txt <span style='color:#111;'> 79B </span>","children":null,"spread":false},{"title":"聚类5结果.png <span style='color:#111;'> 22.17KB </span>","children":null,"spread":false}],"spread":true},{"title":"(可视化)kmeans.py <span style='color:#111;'> 499B </span>","children":null,"spread":false},{"title":"2cen]","children":[{"title":"c2exm2.txt <span style='color:#111;'> 119B </span>","children":null,"spread":false},{"title":"c2exm1.txt <span style='color:#111;'> 110B </span>","children":null,"spread":false},{"title":"聚类2结果可视化散点图.png <span style='color:#111;'> 19.72KB </span>","children":null,"spread":false},{"title":"聚类2结果.png <span style='color:#111;'> 15.88KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":".gitignore <span style='color:#111;'> 1.76KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 6.08KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】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,【只为小站】 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 【只为小站】 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,zhiweidada#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