Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications

Description

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:

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.

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.

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.

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.









Not all books on AvaxHome appear on the homepage. In order not to miss many of them follow ebooks section (see top of each page on AH) and visit my blog too :)

Disclaimer:
Contents of this page are indexed from this page for search purpose only. All actions are under your responsability. Email us to report illegal contents or external links and we'll remove them immediately.

Please check the description for download links if any or do a search to find alternative books.

Can't Download?
Please search mirrors if you can't find download links for "Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications" in "Description" and someone else may update the links. Check the comments when back to find any updates.

Search Mirrors
Maybe some mirror pages will be helpful, search this book at top of this page or click here to find more info.

1. Ebooks list page : 2644
2. Glenn J. Myatt, ?Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining?
3. Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
4. Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
5. Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
6. Glenn J. Myatt, Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mini
7. Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
8. [share_ebook] Practical Text Mining with Perl (Wiley Series on Methods and Applications in Data Mining)
9. Handbook of Statistics, Volume 24: Data Mining and Data Visualization
10. Java Data Mining: Strategy, Standard, and Practice: A Practical Guide for architecture, design, and implementation (The Morgan Kaufmann Series in Data Management Systems)
11. Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems)
12. [request_ebook] Advanced Data Warehouse Design From Conventional to Spatial and Temporal Applications
13. Data Mining Patterns: New Methods and Applications
14. Data Mining Patterns: New Methods and Applications
15. Data Mining Patterns: New Methods and Applications
16. Multimedia Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)