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Beskrivande textThis text cuts through the technical language of other books to provide an ideal primer for those looking to use data mining in crime and intelligence analysis.(Bookdata)
Recensioner"Dr. Colleen McCue pairs an educational background in neuroscience and psychology with extensive experience in the fields of behavioral science, crime analysis and intelligence gathering to create Data Mining and Predictive Analysis , a must-read for all law enforcement professionals. Within the ever-growing fields of criminal justice and crime analysis, Dr. McCue combines all facets of the public safety community, effortlessly examining techniques in which law enforcement, analysts, and researchers are able to delve deeper through her accessible explanations of relative degrees of data quality, validity and reliability; all essential tools in this modern, technological era." - Arthur E. Westveer (Associate Professor, L. Douglas Wilder School of Government and Public Affairs, Virginia Commonwealth University) "[Data Mining and Predictive Analysis] is a must-read..., blending analytical horsepower with real-life operational examples. Operators owe it to themselves to dig in and make tactical decisions more efficiently, and learn the language that sells good tactics to leadership. Analysts, intell support, and leaders owe it to themselves to learn a new way to attack the problem in support of law enforcement, security, and intelligence operations. Not just a dilettante academic, Dr. McCue is passionate about getting the best tactical solution in the most efficient wayand she uses data mining to do it. Understandable yet detailed, [Data Mining and Predictive Analysis] puts forth a solid argument for integrating predictive analytics into action. Not just for analysts!" - Tim King (Director, Special Programs and Global Business Development, ArmorGroup International Training) "Dr. McCue's clear and brilliant guide to attacking society's greatest threats reveals how to best combine the powers of statistical computation and the experience of domain experts. Her emphasis on understanding the essential data through fieldwork and close partnership with the end users of the information is vital to making the discovered patterns "actionable". Anyone seeking to harness the power of data mining to "connect the dots" or "find needles in a haystack" will benefit from this lively and reliable book packed with practical techniques proven effective on tough real-world problems." - Dr. John Elder (Chief Scientist of Elder Research, Inc., www.datamininglab.com)(Bookdata)
ÖvrigtColleen McCue received a Ph.D. in experimental psychology in 1989. The program of study included significant instruction in advanced and multivariate statistical analysis. Currently, she is the Program Manager of the Richmond, Virginia Police Department. She maintains an active research program and began exploring the use of computer modeling in the analysis of violent crime approximately six years ago. She recently published a white paper outlining work with data mining and predictive analytics in crime and intelligence analysis, and has a manuscript in press in the same area with the FBIs Law Enforcement Bulletin. She has written for and lectured to law enforcement audiences regularly at the state, local and federal level. As a direct result of this experience she can bring a unique understanding of the existing skill set and the approach necessary to convey information to this demographic.(Bookdata)
InnehållsförteckningIntroductory Section Chapter 1: Basics Chapter 2: Domain Expertise Chapter 3: Data mining Methods Chapter 4: Process Models for Data Mining and Analysis Chapter 5: Data Chapter 6: Operationally-relevant preprocessing Chapter 7: Identification, Characterization and Modeling Chapter 8: Evaluation Chapter 9: Operationally-Actionable Output Applications Chapter 10: Normal Crime Chapter 11: Behavioral Analysis of Violent Crime Chapter 12: Risk and Threat Assessment Case Examples Chapter 13: Deployment Chapter 14: Surveillance Detection Advanced Concepts and Future Trends Chapter 15: Advanced Concepts in Data Mining Chapter 16: Future Trends(Bookdata)
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