Making Sense of Data II 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Making Sense of Data II

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Glenn J. Myatt 作者
John Wiley & Sons Inc
譯者
2009-3-10 出版日期
291 頁數
$79.95 價格
Paperback
叢書系列
9780470222805 圖書編碼

Making Sense of Data II 在線電子書 圖書標籤: 數據可視化  DataMining  統計  數據分析  Visualization  科普  數據處理  原始/圖形思維   


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Making Sense of Data II 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Making Sense of Data II 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Making Sense of Data II 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Making Sense of Data II 在線電子書 著者簡介


Making Sense of Data II 在線電子書 著者簡介


Making Sense of Data II 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Making Sense of Data II 在線電子書 圖書描述

A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques

This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences.

Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis:

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Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces.

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Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed.

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Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes.

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Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios.

Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online.

With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.

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