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Titlebook: Information-Statistical Data Mining; Warehouse Integratio Bon K. Sy,Arjun K. Gupta Book 2004 Springer Science+Business Media New York 2004

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发表于 2025-3-21 19:49:41 | 显示全部楼层 |阅读模式
书目名称Information-Statistical Data Mining
副标题Warehouse Integratio
编辑Bon K. Sy,Arjun K. Gupta
视频videohttp://file.papertrans.cn/467/466024/466024.mp4
丛书名称The Springer International Series in Engineering and Computer Science
图书封面Titlebook: Information-Statistical Data Mining; Warehouse Integratio Bon K. Sy,Arjun K. Gupta Book 2004 Springer Science+Business Media New York 2004
描述.Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics. is written to introduce basic concepts, advanced research techniques, and practical solutions of data warehousing and data mining for hosting large data sets and EDA. This book is unique because it is one of the few in the forefront that attempts to bridge statistics and information theory through a concept of patterns. .Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics. is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.
出版日期Book 2004
关键词Code; Information; Mathcad; classification; data analysis; data mining; information theory; performance; sta
版次1
doihttps://doi.org/10.1007/978-1-4419-9001-3
isbn_softcover978-1-4613-4755-2
isbn_ebook978-1-4419-9001-3Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 2004
The information of publication is updating

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Bayesian Nets & Model Generation,Bayesian networks are graphical models that capture the probability dependency relationships among random variables. The probability dependency relationships are encoded as the likelihoods of event associations in terms of conditional probabilities.
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The Springer International Series in Engineering and Computer Sciencehttp://image.papertrans.cn/i/image/466024.jpg
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978-1-4613-4755-2Springer Science+Business Media New York 2004
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Data Warehouse Basics, activities towards a better understanding of an organization’s specific mission/activity. Therefore, data warehousing may be construed as a collection of technologies to aid (organizational) decision-making and/or strategic planning when it is used in conjunction with data mining technologies.
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Pattern Inference & Model Discovery, inference is model based. In other words, we need probability model(s) in order to conduct pattern-based inference. In chapter 10 we will discuss one kind of probability models — Bayesian networks. It has a graphical representation for the mathematical structure of the probability models.
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Case Study 2: Financial Data Analysis,and General Dynamics. The information theoretic approach described in chapter 7 is used to estimate the number of change points as well as their locations. Model selection methodology, using Schwarz Information Criterion, is promulgated to solve the difficult problem of change point analysis.
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