Description: 基于决策树和贝叶斯的预测分析器，可以对数据库中的数据集通过训练学习后根据训练结果进行信息预测。-Based on Decision Tree and Bayesian prediction of the analyzer can be in the database data sets through training to learn the results after the training information in accordance with prediction. Platform: |
Size: 3811328 |
Author:季芳 |
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Description: 对人脸识别的贝叶斯方法ML中相似度计算公式进行了简化，对数据集的训练和人脸图像的预处理进
行了修改，提出了一种改进的贝叶斯人脸识另1】算法SML。在FERET人脸图像库的子集和南大人脸图像实验库上对
识别算法进行了测试和比较。实验表明，SML算法提高了ML算法的效率，克服了ML算法计算效率不高的缺陷，而
且SML的识别效率明显高于PCA方法。-Bayesian face recognition method on the ML in the similarity formula has been simplified, the data set of training and pre-processing face images were modified, an improved understanding of Bayesian Face Ling 1】 algorithm SML. In the FERET face image database a subset of the Southern adults face image recognition algorithm on the experimental database was tested and compared. Experiments show that, SML algorithm improves the efficiency of ML algorithm, ML algorithm overcomes the shortcomings of high efficiency, and the recognition rate significantly higher than SML PCA method. Platform: |
Size: 262144 |
Author:dmay |
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Description: 基于朴素贝叶斯的分类练习，在UCI数据库中的breast数据集上进行的测试-Bayesian classification based on practice, in the UCI database data set on breast test Platform: |
Size: 1024 |
Author:王善民 |
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Description: 这是《数据挖掘原理与应用—SQL Server 2008数据库》的随书SQL语句、源代码和Excel范例文件，基于DMX，代码主要包括对SQL Server 2008和Excel 2007中已经集成好的数据挖掘算法的应用， 如贝叶斯聚类、决策树、时序、聚类、序列聚类、关联规则、神经网络、逻辑回归、OLAP立方体的等算法，具有极高的使用价值。-This is the " Principles and Applications of data mining-SQL Server 2008 database" SQL statements with the book, the source code and Excel sample file, based on the DMX, the code mainly on the SQL Server 2008 and Excel 2007 have been integrated in the application of good data mining algorithms such as Bayesian clustering, decision tree, time series, clustering, sequence clustering, association rules, neural network, logistic regression, OLAP cubes and other algorithms, with a high use value. Platform: |
Size: 27428864 |
Author:吴 |
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Description: 本文以网上购书为例,对基于数据挖掘技术的个性化的网上购书系统进行了研究设计。网站主要实现了注册登录模块功能，书籍根据分类和书名搜索功能，查看书籍详细信息功能，利用关联规则，贝叶斯分类算法向用户推荐用户可能感兴趣或对用户有用的书的模块，加入购物车，购买模块。前面的功能只要是前台的显示，在服务器端，使用SQL server2005作为数据库，由后台逻辑控制模块把数据提交给合适的功能模块和算法模块，从而组合成一个完整的系统。在这个系统中，页面是使用JSP来动态生成的，后台使用的是Servlet控制整个流程。-In this paper, online bookstores, for example, based on data mining technology, personalized online book system studied design. The main achievement of the registration website login module functions, books based on classification and title search, view book details function, using association rules, Bayesian classification algorithm recommended to the user or the user may be interested in the book useful to the user module, adding cart and purchase modules. Function as long as the front is the front of the display, on the server side, use SQL server2005 as a database, from the background logic control module the data submitted to the appropriate functional modules and algorithms modules to be combined into a complete system. In this system, the page is dynamically generated using JSP, Servlet backend uses to control the entire process. Platform: |
Size: 3885056 |
Author:invest |
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Description: 《深入浅出数据分析》以类似“章回小说”的活泼形式，生动地向读者展现优秀的数据分析人员应知应会的技术：数据分析基本步骤、实验方法、最优化方法、假设检验方法、贝叶斯统计方法、主观概率法、启发法、直方图法、回归法、误差处理、相关数据库、数据整理技巧；正文以后，意犹未尽地以三篇附录介绍数据分析十大要务、R工具及ToolPak工具，在充分展现《深入浅出数据分析》目标知识以外，为读者搭建了走向下一步深入研究的桥梁。
《深入浅出数据分析》构思跌宕起伏，行文妙趣横生，无论读者是职场老手，还是业界新人；无论是字斟句酌，还是信手翻阅，都能跟着文字在职场中走上几回，体味数据分析领域的乐趣与挑战。("Data analysis" similar to "novels" lively form, vividly to readers excellent data analysis personnel should be aware of the data analysis technology: basic steps, experiment method, optimization method and hypothesis testing methods, Bayesian statistics method, subjective probability method, heuristic method, histogram method, regression method, error handling, database, data processing skills; text, enough to three appendix introduces the data analysis of ten major priority, R tools and ToolPak tools in the show "simple data analysis" target knowledge, to build a bridge to the next study for readers.
"Data analysis" concept of ups and downs, the workplace is full of wit and humour, regardless of whether the reader or industry veteran, whether it is new; carefully worded, or Xinshou read, followed by the text in the workplace can go a few times, fun and challenge in the field of data analysis experience.) Platform: |
Size: 5291008 |
Author:zazuimingyue |
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