Contributors from the computer and information sciences survey recent developments in predictive analytics, including methods for forecasting, modeling, and understanding time series, detecting anomalies and emerging issues, inferring causality over time, presenting identified patterns interactively, and validating analytical models using real-world historical data. Among the topics are ubiquitous management methodology for predictive maintenance in medical devices, spatial and temporal predicting analysis for energy network optimization, using machine learning algorithms to protect an intranet from cyberattack, verifying a user's identity using a frequentist probability model of keystroke intervals, and predicting analytics of money supply in India.
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