Description: weka是机器学习和数据挖掘领域最有影响力的开源项目之一，大量实用的代码-weka is machine learning and data mining areas of the most influential open source projects, a lot of practical code Platform: |
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Author:null |
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Description: weka是机器学习和数据挖掘领域最有影响力的开源项目之一，大量实用的代码-weka is machine learning and data mining areas of the most influential open source projects, a lot of practical code Platform: |
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Author:null |
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Description: 可挖掘负关联规则的FP_growth算法:将负项目扩展到原始数据集，同正项目一样看成普通项目（该过程已集成到程序中），然后使用FP_growth算法挖掘含负项目的一般化频繁项集-Can be a negative association rules mining algorithm FP_growth: negative item will be extended to the original data sets,同正projects as ordinary items (the process has been integrated into the program), then use the algorithm FP_growth excavation projects with negative generalized frequent itemsets Platform: |
Size: 3572736 |
Author:耿晓斐 |
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Description: 主要功能 基础数据库建设 数据导入导出－建库 数据仓库－数据挖掘（查询、排序、打印、统计、报表、批处理 数据管理－－数据新增、修改等审核流程 综合考评 年度统计 门户管理 功能介绍 人员管理子系统 提供了人员、机构的各种信息。能够对人员增加、删除、修改、通用性查找、自定义搜索条件和显示字段生成模板进行智能化查找。能够对人员信息进行如年龄范围，指定职务等条件的文字统计和图形统计和报表，可以将人员信息导出成Excel格式。 机构管理子系统 对机构进行增加、删除、更新、指定上级机构、从人员部分指定机构人员。 项目管理子系统 该子系统主要针对各种来源的项目提供了管理功能。能提供各种项目的信息，对项目实现增加、取消、修改、查找等功能。并能显示各种项目的申报、立项、中检、终结等状态。 对项目各种经费进行增加、取消、修改、查找动作。 项目申报，对校级项目提供项目新增、删除、立项、撤销、中检、终结动作。提供了社科类项目申请模板，并且能和社科网提供接口，实现适时交-Basis for the construction of the main functions of the database Data Import Export- Data Warehouse Database- Data Mining (query, sort, print, statistics, reports, batch data management- data to add, amend the comprehensive evaluation process, such as audited annual statistics portal management capabilities introduced personnel management system has provided staff, all kinds of information agencies. able to staff to add, delete, modify, universal search, custom search criteria and display the fields of intelligent search generated template. able to staff the scope of information such as age to specify the conditions of their duties, such as text and graphical statistics and statistical reports, staff information can be exported into Excel format. agency management system for agencies to add, delete, update, specify the parent body, from the staff members of the designated part. project management sub- system, the subsystems of major projects for a variety of sources to provide the Platform: |
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Author:ctt |
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Description: 《实用数据挖掘》
本书对面向应用的数据挖掘方法进行了清晰的阐述，包括经典的多元统计方法、贝叶斯多元统计方法、基于机器学习的数据挖掘方法和基于计算的数据挖掘方法等。介绍了数据挖掘领域中许多最新的研究成果，如关联规则、序列规则、图示马尔可夫模型、基于存储的推理、信用风险和Web挖掘等。并详细介绍了选自实际工业项目的6个应用实例，强调了数据挖掘方法的实用性。 本书主要面向计算机科学、信息管理、应用统计学和经济学等专业的高年级本科生和研究生。对实际从事海量数据分析和处理的技术人员也有很好的指导作用和参考价值。 -Application-oriented book on data mining methods were clearly described, including the classic multivariate statistical methods, Bayesian multivariate statistical methods, data mining based on machine learning methods and calculations based on data mining methods. The field of data mining are introduced many of the latest research results, such as association rules, sequence rules, icons, Markov model, based on the storage of reasoning, credit risk, and Web mining. And gave details of the actual industrial projects selected from the six examples, emphasizing the usefulness of data mining methods. Book is mainly for computer science, information management, applied statistics and economics, and other professional undergraduate and graduate students. Actually engaged in massive data for analysis and processing of the technical staff are also very good guidance and reference value.
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Author:showna |
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Description: 本书共15章，分两个部分：基础篇、实战篇。基础篇介绍了数据挖掘的基本原理，实战篇介绍了一个个真实案例，通过对案例深入浅出的剖析，使读者在不知不觉中通过案例实践获得数据挖掘项目经验，同时快速领悟看似难懂的数据挖掘理论。读者在阅读过程中，应充分利用随书配套的案例建模数据，借助相关的数据挖掘建模工具，通过上机实验，以快速理解相关知识与理论。(There are 15 chapters in this book, which are divided into two parts: the basic chapter and the actual combat chapter. The basic chapter introduces the basic principles of data mining, and the actual combat section introduces a real case. Through the analysis of the cases, the readers can gain the experience of data mining projects through the case practice unconsciously, and quickly understand the seemingly difficult theory of data mining. In the process of reading, readers should make full use of the case modeling data provided with the book, with the help of relevant data mining modeling tools, and through computer experiments, to quickly understand the relevant knowledge and theory.) Platform: |
Size: 49031168 |
Author:zhaolong2020 |
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Search - data mining projects