- Häftad (Paperback)
- Antal sidor
- illustrated ed
- 236 x 190 x 22 mm
- Antal komponenter
- 860 g
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Data Mining and Predictive Analysis
Intelligence Gathering and Crime Analysis
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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
Recensioner i media
"[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 way-and 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)
Bloggat om Data Mining and Predictive Analysis
Dr. Colleen McCue is the Senior Director of Social Science and Quantitative Methods at DigitalGlobe. Her areas of expertise within , in the applied public safety and national security environment include the application of data mining and predictive analytics to the analysis of crime and intelligence data, with particular emphasis on deployment strategies; surveillance detection; threat and vulnerability assessment; geospatial predictive analytics; computational modeling and visualization of human behavior; Human, Social, Culture and Behavior (HSCB) modeling and analysis; crisis and conflict mapping; and the behavioral analysis of violent crime in support of anticipation and influence.
Introductory 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