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Conformal Prediction for Reliable Machine Learning: Theory, - download pdf or read online

By Vineeth Balasubramanian,Shen-Shyang Ho,Vladimir Vovk

The conformal predictions framework is a contemporary improvement in computer studying that could affiliate a competent degree of self assurance with a prediction in any real-world trend popularity program, together with risk-sensitive functions equivalent to scientific prognosis, face reputation, and fiscal possibility prediction. Conformal Predictions for trustworthy desktop studying: thought, diversifications and Applications captures the elemental conception of the framework, demonstrates how you can use it on real-world difficulties, and offers numerous variations, together with lively studying, switch detection, and anomaly detection. As practitioners and researchers worldwide practice and adapt the framework, this edited quantity brings jointly those our bodies of labor, delivering a springboard for additional study in addition to a guide for software in real-world problems.

  • Understand the theoretical foundations of this crucial framework which can supply a competent degree of self belief with predictions in computing device learning
  • Be in a position to follow this framework to real-world difficulties in numerous desktop studying settings, together with class, regression, and clustering
  • Learn potent methods of adapting the framework to more moderen challenge settings, corresponding to lively studying, version choice, or swap detection

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Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications by Vineeth Balasubramanian,Shen-Shyang Ho,Vladimir Vovk


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