Feature importance methods unveiling the cross-sensitive response of an integrated sensor array to quantify major cations in drinking water-Reference-Cited by-同舟云学术

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Feature importance methods unveiling the cross-sensitive response of an integrated sensor array to quantify major cations in drinking water

Published:2022-10-30 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Sensors
language:
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Author:

Gabrieli Gianmarco¹,Muszynski Michal¹,Ruch Patrick W.¹

Affiliation:

1. IBM Research Europe,Rüschlikon,Switzerland,8803

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9966996/9966997/09967157.pdf?arnumber=9967157

Reference20 articles.

1. Combining an Integrated Sensor Array with Machine Learning for the Simultaneous Quantification of Multiple Cations in Aqueous Mixtures

2. Quantile regression forests;meinshausen;Journal of Machine Learning Research,2006

3. Gaussian processes in machine learning;rasmussen;Machine Learning Summer School,2003

4. Bayesian Interpolation

5. Multi-task feature learning;evgeniou;Advances in neural information processing systems,2007

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