by
Simovici, Dan A.
Call Number
006.3
Publication Date
2012
Summary
This comprehensive volume presents the foundations of linear algebra ideas and techniques applied to data mining and related fields. Linear algebra has gained increasing importance in data mining and pattern recognition, as shown by the many current data mining publications, and has a strong impact in other disciplines like psychology, chemistry, and biology. The basic material is accompanied by more than 550 exercises and supplements, many accompanied with complete solutions and MATLAB applications.
Format:
Electronic Resources
Relevance:
134467.9531
by
Han, Jiawei.
Call Number
005.741 22
Publication Date
2006
Summary
Highly anticipated second edition of the definitive reference on data mining by the top authority.
Format:
Electronic Resources
Relevance:
126784.4219
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by
Refaat, Mamdouh.
Call Number
006.312 22
Publication Date
2007
Summary
Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little how to information? And are you, like most analysts, preparing the data in SAS? This book is intended to fill this gap as your source of practical recipes. It introduces a framework for the process of data preparation for data mining, and presents the detailed implementation of each step in SAS. In addition, business applications of data mining modeling require you to deal with a large number of variables, typically hundreds if not thousands. Therefore, the book devotes several chapters to the methods of data transformation and variable selection. FEATURES * A complete framework for the data preparation process, including implementation details for each step. * The complete SAS implementation code, which is readily usable by professional analysts and data miners. * A unique and comprehensive approach for the treatment of missing values, optimal binning, and cardinality reduction. * Assumes minimal proficiency in SAS and includes a quick-start chapter on writing SAS macros. * CD includes dozens of SAS macros plus the sample data and the program for the book's case study.
Format:
Electronic Resources
Relevance:
126784.3672
by
Motoda, Hiroshi.
Call Number
006.3 22
Publication Date
2002
Summary
Focusing on data mining, this work is a joint effort from researchers in Japan, and includes a report on the forefront of data collection, user-centred mining and user interaction/reaction. It offers an overview of modern solutions with real-world applications, sharing hard-learned experiences.
Format:
Electronic Resources
Relevance:
114682.8672
by
ClickView (Firm)
Call Number
XX(302365.1)
Summary
Incredibly large volumes of data are generated on a daily basis. Within that data hides information that can prove extremely valuable on a social, economic, political or environmental level. But to unearth the 'gold' the data needs to be mined. This interview led programme explains exactly what data mining is, the data collected, uses of data mining, the data processes involved and tips for successful data mining. We talk with world leaders in the field, including Doug Campbell, director of Deloitte Analytics, John Elder Chief scientist of Elder Research, and Peter O'Hanlon, director of Institute of Analytics Professionals of Australia. A programme for senior secondary and TAFE in business, IT and the social sciences, it provides great insight into the rapidly developing world of data mining.
Format:
Other
Relevance:
114680.0313
by
McCue, Colleen.
Call Number
363.256 22
Publication Date
2007
Summary
It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforcement professionals, but also provides real-world examples showing how data mining has identified crime trends, anticipated community hot-spots, and refined resource deployment decisions. In this book Dr. McCue describes her use of "off the shelf" software to graphically depict crime trends and to predict where future crimes are likely to occur. Armed with this data, law enforcement executives can develop "risk-based deployment strategies," that allow them to make informed and cost-efficient staffing decisions based on the likelihood of specific criminal activity. Knowledge of advanced statistics is not a prerequisite for using Data Mining and Predictive Analysis. The book is a starting point for those thinking about using data mining in a law enforcement setting. It provides terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis, which law enforcement and intelligence professionals can tailor to their own unique situation and responsibilities. * Serves as a valuable reference tool for both the student and the law enforcement professional * Contains practical information used in real-life law enforcement situations * Approach is very user-friendly, conveying sophisticated analyses in practical terms.
Format:
Electronic Resources
Relevance:
109799.6328
by
Wittek, Peter, author.
Call Number
530.12 23
Publication Date
2014
Summary
"Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications. Bridges the gap between abstract developments in quantum computing with the applied research on machine learning Provides the theoretical minimum of machine learning, quantum mechanics, and quantum computing Gives step-by-step guidance to a broader understanding of this emergent interdisciplinary body of research."
Format:
Electronic Resources
Relevance:
109795.7109
by
Wong, Stephen T. C.
Call Number
572 22
Publication Date
2006
Summary
This timely book identifies and highlights the latest data mining paradigms to analyze, combine, integrate, model and simulate vast amounts of heterogeneous multi-modal, multi-scale data for emerging real-world applications in life science. The cutting-edge topics presented include bio-surveillance, disease outbreak detection, high throughput bioimaging, drug screening, predictive toxicology, biosensors, and the integration of macro-scale bio-surveillance and environmental data with micro-scale biological data for personalized medicine. This collection of works from leading researchers in the.
Format:
Electronic Resources
Relevance:
109791.8047
by
Cerrito, Patricia B.
Call Number
610.285 23
Publication Date
2011
Summary
Decisions regarding the risks involved in medical treatments must belong to patients and their physicians - after all, it is the patient's health and life which is at stake. But patients will not be equipped for this decision-making process if they cannot be given some idea as to the risks and benefits of treatment. Such risks are generally estimated by a consensus panel of specialist physicians using supporting medical literature. Unfortunately, this literature does not always provide a good estimate of risk, particularly in the case of rare occurrences. This book demonstrates statistical tec.
Format:
Electronic Resources
Relevance:
105490.1016
by
Popescu, Mihail, 1962-
Call Number
610.285 22
Publication Date
2009
Format:
Electronic Resources
Relevance:
105490.0313
by
Soares, Carlos.
Call Number
006.312 22
Publication Date
2010
Summary
Data mining is already incorporated into the business processes in many sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This technology is well established in applications such as targeted marketing, customer churn detection and market basket analysis. It is also emerging as an important technology in a wide range of new application areas, such as social media, social networks and sensor networks. These areas pose new challenges both in terms of the nature of available data and the underlying support technology. This book contains extended v.
Format:
Electronic Resources
Relevance:
101657.3984
by
Bifet, Albert.
Call Number
006.312 22
Publication Date
2010
Summary
Contributes to the subject of mining time-changing data streams and addresses the design of learning algorithms for this purpose. This book introduces contributions on several different aspects of the problem, identifying research opportunities and increasing the scope for applications.
Format:
Electronic Resources
Relevance:
98210.8828
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