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Ensemble machine learning methods and applications

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  • "It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed âensemble learningâ|#x009D; by researchers in computational intelligence and machine learning, it is known to improve a decision systemâs robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as âboostingâ|#x009D; and ârandom forestâ|#x009D; facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike."

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  • "Ressources Internet"
  • "Electronic books"
  • "Electronic books"@en

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  • "Ensemble Machine Learning: Methods and Applications"
  • "Ensemble Machine Learning : Methods and Applications"
  • "Ensemble machine learning methods and applications"
  • "Ensemble machine learning methods and applications"@en
  • "Ensemble Machine Learning"@en
  • "Ensemble Machine Learning Methods and Applications"
  • "Ensemble Machine Learning Methods and Applications"@en
  • "Ensemble machine learning : methods and applications"
  • "Ensemble machine learning : methods and applications"@en

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