Fast Data-Driven Greedy Sensor Selection for Ridge Regression

We propose a data-driven sensor-selection algorithm for accurate estimation of the target variables from the selected measurements. The target variables are assumed to be estimated by a ridge-regression estimator, which is trained based on the data. The proposed algorithm greedily selects sensors fo...

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Vydané v:	IEEE sensors journal Ročník 25; číslo 6; s. 10030 - 10045
Hlavní autori:	Sasaki, Yasuo, Yamada, Keigo, Nagata, Takayuki, Saito, Yuji, Nonomura, Taku
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 15.03.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Algorithms Computational modeling Cost function Datasets Estimation Greedy algorithms Intelligent sensors Keywords Greedy algorithm Linear programming Linear systems Overfitting Parameters Regularization ridge regression sensor selection Sensors Training Vectors
ISSN:	1530-437X, 1558-1748
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