Machine-learning:葡萄酒品质预测

上传者: 42150360 | 上传时间: 2022-04-11 11:30:04 | 文件大小: 1.12MB | 文件类型: ZIP
机器学习葡萄酒质量预测 ================ 目的 找到一个合适的分类器来预测葡萄酒类型和葡萄酒质量。 给定数据 数据来自葡萄牙的“Vinho Verde”葡萄酒,它具有 11 种不同的化学特性。 葡萄酒类型包括白葡萄酒和红葡萄酒,葡萄酒质量由葡萄酒专家划分为 1(好)和 7(差)。 给定的数据集分为 5000 个训练样本和 1000 个测试样本,并存储在两个 .csv 文件中。 它们每个都有 13 列,包括 11 个化学测量值和两列描述葡萄酒类型和质量的列。 葡萄酒类型预测

文件下载

资源详情

[{"title":"( 23 个子文件 1.12MB ) Machine-learning:葡萄酒品质预测","children":[{"title":"Machine-learning-master","children":[{"title":"winetype","children":[{"title":"visualize.m <span style='color:#111;'> 189B </span>","children":null,"spread":false},{"title":"wineType.m <span style='color:#111;'> 1.82KB </span>","children":null,"spread":false},{"title":"scorecomp.m <span style='color:#111;'> 865B </span>","children":null,"spread":false},{"title":"typetrain.m <span style='color:#111;'> 1.32KB </span>","children":null,"spread":false},{"title":"csvmtrain.m <span style='color:#111;'> 693B </span>","children":null,"spread":false}],"spread":true},{"title":"lib","children":[{"title":"BayesTrain.m <span style='color:#111;'> 217B </span>","children":null,"spread":false},{"title":"PCA.m <span style='color:#111;'> 330B </span>","children":null,"spread":false},{"title":"ConvertCate.m <span style='color:#111;'> 411B </span>","children":null,"spread":false},{"title":"accuracycomp.m <span style='color:#111;'> 535B </span>","children":null,"spread":false},{"title":"maxvalues.m <span style='color:#111;'> 267B </span>","children":null,"spread":false},{"title":"computeFScore.m <span style='color:#111;'> 353B </span>","children":null,"spread":false},{"title":"fScore.m <span style='color:#111;'> 547B </span>","children":null,"spread":false}],"spread":true},{"title":"winequality","children":[{"title":"qualityScores.m <span style='color:#111;'> 240B </span>","children":null,"spread":false},{"title":"knnwhiteredtrain.m <span style='color:#111;'> 2.22KB </span>","children":null,"spread":false},{"title":"wineQuality.m <span style='color:#111;'> 1.30KB </span>","children":null,"spread":false},{"title":"multisvm.m <span style='color:#111;'> 931B </span>","children":null,"spread":false},{"title":"kcrossvalidation.m <span style='color:#111;'> 1.20KB </span>","children":null,"spread":false},{"title":"knn.m <span style='color:#111;'> 944B </span>","children":null,"spread":false},{"title":"qualitytrain.m <span style='color:#111;'> 973B </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 620B </span>","children":null,"spread":false},{"title":"finalreport.pdf <span style='color:#111;'> 637.64KB </span>","children":null,"spread":false},{"title":"data","children":[{"title":"testdataset.csv <span style='color:#111;'> 194.83KB </span>","children":null,"spread":false},{"title":"trainingdataset.csv <span style='color:#111;'> 973.78KB </span>","children":null,"spread":false}],"spread":true}],"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