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Conformal Prediction for Reliable Machine Learning

financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory;

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Algorithmic Learning in a Random World

This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature;

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Conformal and Probabilistic Prediction with Applications

This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with;

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Machine Learning for Protein Subcellular Localization Prediction

strategies for virus, plant, and eukaryote species. Three machine learning tools are introduced to improve classification refinement, feature;

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Intelligent Learning Systems

, the computational learning theory, and the use of statistics for the purpose of learning - based on previously available data.Extremely;

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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind;

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Kubeflow for Machine Learning From Lab to Production

If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides;

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Statistical Issues in Machine Learning Towards Reliable Split Selection and Variable Importance Measures

Statistical Issues in Machine Learning Towards Reliable Split Selection and Variable Importance Measures is een boek van Strobl, Carolin;

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Grammar Based Feature Generation for Time Series Prediction

This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation;

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Prediction Of Diabetes Blood Sugar Levels Using Machine Learning

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Applied Genetic Programming and Machine Learning

Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly;

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Applied Genetic Programming and Machine Learning

Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications. Reflecting rapidly;

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Statistical Learning and Data Sciences

selected from 59 submissions. The papers are organized in topical sections on statistical learning and its applications, conformal prediction and;

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Analysis on Prediction of Swine Flu Using Machine Learning Algorithms

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Machine Learning for Networking

learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection, optimization and new;

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Machine Learning for Networking

learning for network slicingoptimization, 5G system, user behavior prediction, multimedia, IoT, securityand protection, optimization and new;

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Machine Learning Approaches for Urban Computing

prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It;

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Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making;

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Algorithms in Machine Learning Paradigms

applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning;

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Algorithms in Machine Learning Paradigms

applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning;

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Machine Learning Applications for Accounting Disclosure and Fraud Detection

is provided towards the prediction of the actual financial performance of the business activity. Machine Learning Applications for Accounting;

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Machine Learning for Networking: First International Conference, Mln 2018, Paris, France, November 27-29, 2018, Revised Selected Papers

for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection;

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R Deep Learning Essentials

prediction Who This Book Is For This book caters to aspiring data scientists who are well versed with machine learning concepts with R and are;

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Oracle Business Intelligence with Machine Learning

representations of input data suitable for a given prediction problem. This book focuses on the practical aspects of implementing machine learning;

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Statistical Learning and Data Science

prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including;

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Statistical Learning and Data Science

prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including;

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Machine Learning in Radiation Oncology

This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory;

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