Sebanyak 49 item atau buku ditemukan

Production/operations Management

Concepts and Situations

COWE CUP 50 142 STERL. COWE SAUC 50 142 STERL. COWE SALA 50 142
STERL. COVE BREA 50 142 STANFORD CT.20 50 709 STANFORD CT.OWA 50
709 STANFORD COURT 50 709 ROTHSCHILD 20 P 50 709 CARLYLE 5 PC.

Konsep-konsep probabilitas dalam perencanaan dan perancangan rekayasa

prinsip-prinsip dasar, jilid 1 (Probability concepts in engineering planning and design

Strategic Supply Chain Design

Theory, Concepts and Applications

practice, the textual definition of logistics management has permanently been
extended since the early 1960's. The prevailing definitions range from the
primary view of logistics as an operational business function encompassing the
transportation, storage and handling of goods to the recent perception of logistics
as a systemic or integral perspective of management.17 In this contemporary
understanding logistics means more than a mere operational business function.
The notion of ...

Migrant women and urban labour market

concepts and case studies of problems, gains, and losses

With reference to Madras, Coimbatore, and Tiruppur cities of India.

With reference to Madras, Coimbatore, and Tiruppur cities of India.

Data warehousing and mining

concepts, methodologies, tools, and applications

"This collection offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing. With more than 300 chapters contributed by over 575 experts from around the globe, this authoritative collection will provide libraries with the essential reference on data mining and warehousing"--Provided by publisher.

offer a broad overview of procedures and methods essential to data mining. The
expertly researched contributions within this section also present an essential
introduction to the innumerable applications of data mining and warehousing.

Data Warehousing and Mining

Concepts, Methodologies, Tools, and Applications

"This collection offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing. With more than 300 chapters contributed by over 575 experts from around the globe, this authoritative collection will provide libraries with the essential reference on data mining and warehousing"--Provided by publisher.

"This collection offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing.

Data Mining

Concepts, Methodologies, Tools, and Applications

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way.Data Mining: Concepts, Methodologies, Tools, and Applicationsis a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the currently technological world.

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way.

Data Mining for Business Intelligence

Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner

Learn how to develop models for classification, prediction, and customer segmentation with the help of Data Mining for Business Intelligence In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. Data Mining for Business Intelligence, which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business, uses real data and actual cases to illustrate the applicability of data mining intelligence to the development of successful business models. Featuring XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of data mining techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples are provided to motivate learning and understanding. Data Mining for Business Intelligence: Provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction, exploration, and affinity analysis Features a business decision-making context for these key methods Illustrates the application and interpretation of these methods using real business cases and data This book helps readers understand the beneficial relationship that can be established between data mining and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions.

Data Mining for Business Intelligence: Provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction, exploration, and affinity analysis Features a business decision-making context for ...

Data Mining

Concepts, Models, Methods, and Algorithms

This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades.

Therefore, building a data-mining model is not a straightforward procedure, but a
very sensitive process requiring, in many cases, feedback information for multiple
mining iterations. In the final phase of the data-mining process, when the ...

Contrast Data Mining

Concepts, Algorithms, and Applications

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical, and business domains. Learn from Real Case Studies of Contrast Mining Applications In this volume, researchers from around the world specializing in architecture engineering, bioinformatics, computer science, medicine, and systems engineering focus on the mining and use of contrast patterns. They demonstrate many useful and powerful capabilities of a variety of contrast mining techniques and algorithms, including tree-based structures, zero-suppressed binary decision diagrams, data cube representations, and clustering algorithms. They also examine how contrast mining is used in leukemia characterization, discriminative gene transfer and microarray analysis, computational toxicology, spatial and image data classification, voting analysis, heart disease prediction, crime analysis, understanding customer behavior, genetic algorithms, and network security.

Contrast data mining is an important and focused subarea of data mining. Its aim
is to find interesting contrast patterns that describe significant differences
between datasets satisfying various contrasting conditions. The contrasting
conditions ...