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    Data Mining and Predictive Analysis

    Data Mining and Predictive Analysis

    - Intelligence Gathering and Crime Analysis

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    Bog E-bog
    • Format
    • Bog, paperback
    • Engelsk

    Beskrivelse

    Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis, and operational law enforcement settings.This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics in intelligence and security analysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment.

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  • Vægt970 g
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    10 cm
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    19,1 cm
    23,5 cm

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    Analyst Data mining Evaluation Insight Neural networks Reliability Resource allocation Risk assessment Processing Privacy Characterization Errors Population Case-based reasoning Confirmation Collection OPTIMIZATION Pattern recognition Cloud computing Context Bias Data cyber fieldwork Civil liberties Escalation Comfort zone Criminal Investigative Analysis Prediction Relational data Crowd-sourcing Dissemination Descriptive statistics Accuracy Return on Investment ROI Outcome measures Link Analysis Data imputation Baseline Geolocation Inferential statistics Emerging technology Generalizability Behavioral analysis Geospatial Ensemble Methods Fraud detection Data Exploration 'predictive analytics' Boosting Expert system Discovery Anomaly Detection Deployment Biometrics Confusion Matrix Behavioral segmentation End user actionable output Activity-Based Intelligence (ABI) automated feature extraction calls for service (CFS) Critical Infrastructure Protection (CIP) domain-specific tools Duplication CIA Intelligence Process exploratory graphics Data Partitioning Domain expertise clustering technique geospatial predictive analysis CRoss Industry Standard Process for Data Mining (CRISP-DM) functional interoperability hostile surveillance Human Terrain Heat maps internal norms managed service Expert options False Alarm Kohonen Network models Mitigate motive determination Fourth-Generation Warfare (4WG) nature of the incident or threat fusion center Natural Surveillance nonobvious relationship analysis (NORA) operational requirements place preference recoding rule induction model Prior Probabilities Operationally relevant operational personnel risk-based deployment preoperational surveillance primary gain

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