The first version of this book was a set of lecture notes for a graduate course on data mining and applications in science and technology organized by the Swedish National Graduate School in Scientific Computing (NGSSC). Since then the material has been used and further developed for an undergraduate course on numerical algorithms for data mining and IT at Link¨oping University. This is a second course in scientific computing for computer science students.
2023-02-19 17:04:23 17.93MB pattern recognition
1
Data Structures and Algorithms Made Easy 的 java 版,原书是 c,后来出了 java,基本内容一致,这个 java 版的最新版(第二版)
2023-02-17 22:46:15 35.73MB algorithm Narasimha Karumanchi,
1
[Hsinchun_Chen]_Dark_Web_Exploring_and_Data_Mining the Dark Side of the Web
2023-02-17 17:27:21 10.23MB Data Mining
1
什么是Kam1n0 v2? Kam1n0 v2.x是可扩展的装配管理和分析平台。 它允许用户首先将(大型)二进制文件集合索引到不同的存储库中,并提供不同的分析服务,例如克隆搜索和分类。 通过使用Application的概念,它支持多租户访问和程序集存储库的管理。 应用程序实例包含其自己的专用存储库,并提供专门的分析服务。 考虑到反向工程任务的多功能性,Kam1n0 v2.x服务器当前提供三种不同类型的克隆搜索应用程序: Asm-Clone , Sym1n0和Asm2Vec以及基于Asm2Vec的可执行分类。 可以将新的应用程序类型进一步添加到平台。 用户可以创建多个应用程序实例。 可以在特定的用户组之间共享应用程序实例。 应用程序存储库的读写访问权限和开/关状态可以由应用程序所有者控制。 Kam1n0 v2.x服务器可以使用多个共享资源池同时为应用程序提供服务。 Kam1n0由和在加
1
bdvis 关于 使用R的生物多样性数据可视化。此程序包提供了一组通过R可视化生物多样性发生数据的功能。请查看描述程序包Barve,V。和J. Otegui的论文。 2016年。bdvis:在R. Bioinformatics:btw333中可视化生物多样性数据。 该软件包的开发从Google Summer of Code项目开始。 安装 install.packages( " bdvis " ) require( bdvis ) 软件包bdvis建议 (出于构建示例的目的) [rinat]( ) 当前可用的功能 为了举例,我们将处理使用rinat包获得的一些数据 install.packages( " rinat " ) require( rinat ) # Data download might take some time inat <- get_inat_obs_pr
2023-02-17 12:37:52 39KB r biodiversity-data-visualizations R
1
原始数据在这里 1.观察数据 首先,用Pandas打开数据,并进行观察。 import numpy import pandas as pd import matplotlib.pyplot as plt %matplotlib inline data = pd.read_csv('Folds5x2_pp.csv') data.head() 会看到数据如下所示: 这份数据代表了一个循环发电厂,每个数据有5列,分别是:AT(温度), V(压力), AP(湿度), RH(压强), PE(输出电力)。我们不用纠结于每项具体的意思。 我们的问题是得到一个线性的关系,对应PE是样本输出,而AT/V/
2023-02-17 12:29:32 147KB data mp python
1
solomn数据集是一个比较经典的用于研究VRP相关问题的数据集,其中 https://www.sintef.no/projectweb/top/vrptw/solomon-benchmark/ 给出了关于数据集的基本介绍
2023-02-15 17:44:18 80KB 车辆路径规划问题 数据集 solomn
1
多维与度量数据结构基础 Foundations of Multidimensional and Metric Data Structures Series: The Morgan Kaufmann Series in Computer Graphics Hardcover: 1024 pages Publisher: Morgan Kaufmann; 1 edition (August 22, 2006) Language: English ISBN-10: 0123694469 ISBN-13: 978-0123694461
2023-02-15 11:54:18 7.55MB 计算几何
1
小型金融知识图谱构建流程 小型金融知识图谱构流程示范 小型金融知识图谱构流程示范 1 知识图谱存储方式 2 图数据库neo4j 2.1 下载 2.2 启动 2.2.1 打开 http://localhost:7474 2.2.2 初始账户和密码均为neo4j(host类型选择bolt) 2.2.3 输入旧密码并输入新密码 2.2.3 登录 3. 知识图谱数据准备 3.1 数据接口 3.2 数据获取 3.2.1 股票基本信息 3.2.2 股票持有股东信息 3.2.3 股票概念信息 3.2.4 股票公告信息 3.2.5 财经新闻信息 3.2.6 概念信息 3.2.7 沪股通和深股通成分信息 3.2.8 股票价格信息 3.2.9 tushare免费接口获取股票数据 3.3 数据预处理 3.3.1 统计股票的交易日量众数 3.3.2 计算股票对数收益 3.3.3 股票间对数收益率相关性 4 搭建金融知识图谱 4.1 连接 4.2 读取数据 4.3 填充和去重 4.4 创建实体 4.5 创建关系 5 数据可视化查询(以平安银行为例) 5.1 查看关联
2023-02-14 17:13:23 11.56MB Python Data Analysis
1
Empirical Modeling and Data Analysis for Engineers and Applied Scientists English | 25 July 2016 | ISBN: 3319327674 | 264 Pages This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions. While science is about discovery, the primary paradigm of engineering and “applied science” is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems. That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as “Statistics for Engineers and Scientists” without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models – predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes.
2023-02-14 10:23:35 11.79MB Data Analysis
1