Machine Learning and Non-Linear Dynamics to the Rescue - Shandilya, Sharad
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In this book, new methods of feature extraction, feature selection, stochastic data characterization (modeling), variance reduction, and measures for parametric discrimination are proposed. These methods have implications for data mining (knowledge extraction), machine learning (predictive modeling), and information theory. A novel decision-support system is developed in order to guide intervention during cardiac arrest. The models that form components of this system are built upon knowledge extracted with signal-processing, non-linear dynamic and machine-learning methods.

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Produktbeschreibung
In this book, new methods of feature extraction, feature selection, stochastic data characterization (modeling), variance reduction, and measures for parametric discrimination are proposed. These methods have implications for data mining (knowledge extraction), machine learning (predictive modeling), and information theory. A novel decision-support system is developed in order to guide intervention during cardiac arrest. The models that form components of this system are built upon knowledge extracted with signal-processing, non-linear dynamic and machine-learning methods.
Autorenporträt
Sharad Shandilya has a doctorate in computer science with research interests spanning machine learning, non-linear dynamics and decision theory. He enjoys creating technologies that operate in non-deterministic, non-stationary domains represented by real-world settings with uncertainty abound.