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Contemporary Perspectives in Data Mining Paperback

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Contemporary Perspectives in Data Mining Paperback

Title
Contemporary Perspectives in Data Mining Volume 3 Paperback

Author
Kenneth D. Lawrence,
Ronald Klimberg

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Overview

 

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner...Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups.

Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups

Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.

CONTENTS SECTION I: PREDICTIVE ANALYTICS. Bootstrap Aggregation for Neural Network Forecasting of Supply Chain Order Quantity, Mark T. Leung and Shaotao Pan. Combining Retrospective and Predictive Analytics for More Robust Decision Support, Thomas Ott and Stephan Kudyba. Predictive Analytical Model of the CEO Compensation of Major U.S. Corporate Insurance Companies, Kenneth Lawrence, Gary Kleinman, and Sheila Lawrence. SECTION II: BUSINESS APPLICATIONS. Analyzing Operational and Financial Performance of U.S. Hospitals Using Two-Stage Production Process, Dinesh Pai and Hengameh Hosseini. Digital Disruption: How E-Commerce Is Changing the Grocery Game, Will Greerer, Gregory Smith, David Hyland, and Mark Frolick. The Hazards of Subgroup Analysis in Randomized Business Experiments and How to Avoid Them, B. D. McCullough. Business Intelligence Challenges for Small and Medium-Sized Business: Leveraging Existing Resources, Nick Perrino, Gregory Smith, David Hyland, and Mark Frolick. SECTION III: TOPICS IN DATA MINING. Data Mining Techniques Applied to Outcome Analysis and Validation for the Futures Drug and Alcohol Rehabilitation Center, Virginia Miori and Catherine Cardamone. An Extended H-Index: A New Method to Evaluate Scientists’ Impact, Feng Yang, Xiya Zu, and Zhimin Huang. Why We Need Analytics Grand Rounds, Ronald Klimberg, Richard Pollack, and Richard Herschel. About the Editors.

 

Product Details

 

ISBN-13: 978-1-64113-054-7
Publisher: Information Age Publishing
Publication date: 9/2017
Pages: 168
Image
Contemporary Perspectives in Data Mining Paperback
Price
$45.99
Language
English
Author
Kenneth D. Lawrence,
Ronald Klimberg
ISBN-13
9781641130547
Publisher
Information Age Publishing
Publish Time
Shipping
Flat rate
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10% Discount
Stock level

10

Is Paperback available?
Yes
Paperback
$45.99
Is Hardcover available?
Yes
Hardcover
$85.99
Is Ebook available?
Yes
Ebook
$65
Category
Technology

Is Paperback available?
Yes
Is Hardcover available?
Yes
Is Ebook available?
Yes

Overview

 

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner...Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups.

Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups

Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.

CONTENTS SECTION I: PREDICTIVE ANALYTICS. Bootstrap Aggregation for Neural Network Forecasting of Supply Chain Order Quantity, Mark T. Leung and Shaotao Pan. Combining Retrospective and Predictive Analytics for More Robust Decision Support, Thomas Ott and Stephan Kudyba. Predictive Analytical Model of the CEO Compensation of Major U.S. Corporate Insurance Companies, Kenneth Lawrence, Gary Kleinman, and Sheila Lawrence. SECTION II: BUSINESS APPLICATIONS. Analyzing Operational and Financial Performance of U.S. Hospitals Using Two-Stage Production Process, Dinesh Pai and Hengameh Hosseini. Digital Disruption: How E-Commerce Is Changing the Grocery Game, Will Greerer, Gregory Smith, David Hyland, and Mark Frolick. The Hazards of Subgroup Analysis in Randomized Business Experiments and How to Avoid Them, B. D. McCullough. Business Intelligence Challenges for Small and Medium-Sized Business: Leveraging Existing Resources, Nick Perrino, Gregory Smith, David Hyland, and Mark Frolick. SECTION III: TOPICS IN DATA MINING. Data Mining Techniques Applied to Outcome Analysis and Validation for the Futures Drug and Alcohol Rehabilitation Center, Virginia Miori and Catherine Cardamone. An Extended H-Index: A New Method to Evaluate Scientists’ Impact, Feng Yang, Xiya Zu, and Zhimin Huang. Why We Need Analytics Grand Rounds, Ronald Klimberg, Richard Pollack, and Richard Herschel. About the Editors.

 

Product Details

 

ISBN-13: 978-1-64113-054-7
Publisher: Information Age Publishing
Publication date: 9/2017
Pages: 168

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