Reliable Evapotranspiration Predictions with a Probabilistic Machine Learning Framework

Reliable Classifications with Machine Learning

In the past decades Machine Learning algorithms have been successfully used in several classification problems. While they often significantly outperform domain experts (in terms of classification accuracy or otherwise), they are mostly not being used in practice. A plausible reason for this is that it is difficult to obtain an unbiased estimation of a single classification’s reliability. While...

Estimating Evapotranspiration using Machine Learning Techniques

The measurement of evapotranspiration is the most important factor in irrigation scheduling. Evapotranspiration means loss of water from the surface of plant and soil. Evaporation parameters are being used in studying water balances, water resource management, and irrigation system design and for estimating plant growth and height as well. Evapotranspiration is measured by different methods by ...

Machine Learning A Probabilistic Approach

Machine learning - a probabilistic perspective

All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. Machine learning : a probabilistic perspective / Kevin P. Murphy. p. cm. — (Adaptive computation and machine learning series) Includes bibliographical references a...

Hedging predictions in machine learning

Recent advances in machine learning make it possible to design efficient prediction algorithms for data sets with huge numbers of parameters. This article describes a new technique for ‘hedging’ the predictions output by many such algorithms, including support vector machines, kernel ridge regression, kernel nearest neighbours, and by many other state-of-the-art methods. The hedged predictions ...