Corpus ID: 218684900

# Fast cross-validation for multi-penalty ridge regression

@article{Wiel2020FastCF,
title={Fast cross-validation for multi-penalty ridge regression},
author={M. V. D. Wiel and M. V. Nee and Armin Rauschenberger},
journal={arXiv: Methodology},
year={2020}
}
• Published 2020
• Mathematics, Computer Science
• arXiv: Methodology
Prediction based on multiple high-dimensional data types needs to account for the potentially strong differences in predictive signal. Ridge regression is a simple, yet versatile and interpretable model for high-dimensional data that has challenged the predictive performance of many more complex models and learners, in particular in dense settings. Moreover, it allows using a specific penalty per data type to account for differences between those. Then, the largest challenge for multi-penalty… Expand
2 Citations

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