PRTS:“时间序列的精确和调用”的非官方Python实现-源码

上传者: 42138545 | 上传时间: 2021-05-19 20:03:21 | 文件大小: 106KB | 文件类型: ZIP
时间序列的精度和召回率 的非官方python实现。 经典异常检测主要涉及基于点的异常,这些异常是在单个时间点上发生的。 但是,许多现实世界中的异常是基于范围的,这意味着它们会在一段时间内发生。 受此观察结果的启发,我们提出了一种新的数学模型来评估时间序列分类算法的准确性。 我们的模型扩展了众所周知的“精度”和“召回率”指标以测量范围,同时为特定于域的首选项启用自定义支持。 这是发布的开源软件。 可从下载。 安装 聚酰亚胺 PRTS位于,因此您可以使用pip进行安装。 $ pip install prts 来自github 您也可以使用以下命令进行安装。 $ git clone https://github.com/CompML/PRTS.git $ cd PRTS $ make install # (or make develop) 用法 from prts import

文件下载

资源详情

[{"title":"( 31 个子文件 106KB ) PRTS:“时间序列的精确和调用”的非官方Python实现-源码","children":[{"title":"PRTS-main","children":[{"title":"poetry.lock <span style='color:#111;'> 62.72KB </span>","children":null,"spread":false},{"title":"pyproject.toml <span style='color:#111;'> 593B </span>","children":null,"spread":false},{"title":"data","children":[{"title":"lstm_ad.pred <span style='color:#111;'> 46.83KB </span>","children":null,"spread":false},{"title":"luminol.real <span style='color:#111;'> 46.83KB </span>","children":null,"spread":false},{"title":"greenhouse.pred <span style='color:#111;'> 46.83KB </span>","children":null,"spread":false},{"title":"luminol.pred <span style='color:#111;'> 46.83KB </span>","children":null,"spread":false},{"title":"lstm_ad.real <span style='color:#111;'> 46.83KB </span>","children":null,"spread":false},{"title":"greenhouse.real <span style='color:#111;'> 46.83KB </span>","children":null,"spread":false}],"spread":true},{"title":".github","children":[{"title":"PULL_REQUEST_TEMPLATE.md <span style='color:#111;'> 382B </span>","children":null,"spread":false},{"title":"ISSUE_TEMPLATE","children":[{"title":"custom-template.md <span style='color:#111;'> 454B </span>","children":null,"spread":false}],"spread":true},{"title":"workflows","children":[{"title":"python-package.yml <span style='color:#111;'> 1.16KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"tests","children":[{"title":"test_interfaces.py <span style='color:#111;'> 867B </span>","children":null,"spread":false},{"title":"test_recall.py <span style='color:#111;'> 3.23KB </span>","children":null,"spread":false},{"title":"test_precision_recall.py <span style='color:#111;'> 535B </span>","children":null,"spread":false},{"title":"test_precision.py <span style='color:#111;'> 4.62KB </span>","children":null,"spread":false},{"title":"test_fscore.py <span style='color:#111;'> 1.56KB </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 11.09KB </span>","children":null,"spread":false},{"title":"examples","children":[{"title":"precision_recall_for_time_series.py <span style='color:#111;'> 3.04KB </span>","children":null,"spread":false},{"title":"example.png <span style='color:#111;'> 70.78KB </span>","children":null,"spread":false}],"spread":true},{"title":".gitignore <span style='color:#111;'> 2.22KB </span>","children":null,"spread":false},{"title":"Makefile <span style='color:#111;'> 1.42KB </span>","children":null,"spread":false},{"title":"prts","children":[{"title":"base","children":[{"title":"time_series_metrics.py <span style='color:#111;'> 5.48KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"time_series_metrics","children":[{"title":"recall.py <span style='color:#111;'> 3.08KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"precision.py <span style='color:#111;'> 3.13KB </span>","children":null,"spread":false},{"title":"fscore.py <span style='color:#111;'> 2.33KB </span>","children":null,"spread":false},{"title":"precision_recall.py <span style='color:#111;'> 417B </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 5.94KB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 4.35KB </span>","children":null,"spread":false},{"title":".flake8 <span style='color:#111;'> 473B </span>","children":null,"spread":false}],"spread":false}],"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