![Elastic net regularized regression for time-series analysis of plasma metabolome stability under sub-optimal freezing condition | Scientific Reports Elastic net regularized regression for time-series analysis of plasma metabolome stability under sub-optimal freezing condition | Scientific Reports](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41598-018-21851-7/MediaObjects/41598_2018_21851_Fig1_HTML.jpg)
Elastic net regularized regression for time-series analysis of plasma metabolome stability under sub-optimal freezing condition | Scientific Reports
![Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise | BMC Medical Research Methodology | Full Text Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise | BMC Medical Research Methodology | Full Text](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12874-020-01105-9/MediaObjects/12874_2020_1105_Fig1_HTML.png)
Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise | BMC Medical Research Methodology | Full Text
![Unsupervised dimensionality reduction versus supervised regularization for classification from sparse data | SpringerLink Unsupervised dimensionality reduction versus supervised regularization for classification from sparse data | SpringerLink](https://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs10618-019-00616-4/MediaObjects/10618_2019_616_Fig6_HTML.png)
Unsupervised dimensionality reduction versus supervised regularization for classification from sparse data | SpringerLink
![Genes | Free Full-Text | Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features | HTML Genes | Free Full-Text | Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features | HTML](https://www.mdpi.com/genes/genes-10-00240/article_deploy/html/images/genes-10-00240-g005.png)
Genes | Free Full-Text | Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features | HTML
![Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise | BMC Medical Research Methodology | Full Text Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise | BMC Medical Research Methodology | Full Text](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12874-020-01105-9/MediaObjects/12874_2020_1105_Fig3_HTML.png)