Spring Data JPA学习以及配置步骤

多得分手 允许在scikit的cross_val_score使用多个度量功能的cross_val_score 。 正如已经讨论过的那样，Python的SciKit包含了用于计算估计量评估指标的强大功能（使用cross_val_score ），但在为同一分类器计算多个指标而不进行再次训练时，它似乎失败了。 由于仅接受单个度量标准名称或单个可调用名称的函数的scoring参数而出现问题。 此存储库的模块multiscorer是一种在cross_val_score中使用任意数量的指标的解决方法。 安装 要“安装”模块，只需下载源代码并将其放置在项目的目录中即可。 （或者，下载multiscor

包含工作日和周末的客流数据，近300万条数据，可能进行客流特征分析。

This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies. . Read more... Abstract: This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

Wholesale customers data.csv，二分类常用数据集 Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv Wholesale customers data.csv

xls2csv.bat可以把文件夹下的xls批量转换成CSV文件，csv文件更容易导入R等数据分析软件。

包含Mysql.Data的5个dll文件，.netframe4.0版本。亲自测试引用成功。

Ma 等。 - 2018 - Data-Driven State-Increment Statistical Model and 1

生态学家在历史，当前和未来气候条件下的全球土地利用和土地覆盖（LULC）数据。 欢迎并感谢您访问此存储库！ 世界气候研究计划（WCRP， ://www.wcrp-climate.org/）是解决与气候耦合系统有关的团块的主要组织，提供过去，现在和将来的气候和土地覆盖全球状况的许多产品。 多项计划根据其需求和要求重新分配了这些数据，例如Wordclim（ )、Paleoclim（ )、Ecoclimate（ ） ）等。 土地使用协调项目（LUH ）提供了一套统一的土地使用方案数据集，以所需的格式将土地使用的历史重建与未来的预测平滑地联系在一起基于WCRP产品的地球系统模型（ESM）。 该数据是全球性的，具有约50 km的空间分辨率，涵盖850-2300年，包括土地使用状态，过渡带和mgt层以及若干代表性集中路径（RCP）和社会经济路径（SSP）。 有关数据的更多详细信息，请

Seer: Leveraging Big Data to Navigate the Complexityof Performance Debugging in