Important features of SHAP interpretation. left column: The SHAP value distribution of the 20 most important features. right column: The importance bar chart of the top 20 features.

Important features of SHAP interpretation. left column: The SHAP value distribution of the 20 most important features. right column: The importance bar chart of the top 20 features.

<p>Important features of SHAP interpretation. left column: The SHAP value distribution of the 20 most important features. right column: The importance bar chart of the top 20 features.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Hongqi Feng (14604437) (author)
مؤلفون آخرون:	Qi Nie (5958599) (author), Sen Yang (88300) (author)
منشور في:	2025
الموضوعات:	Genetics Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified regulate gene expression matthew correlation coefficient experimentally validated dataset ensemble learning strategy enhancing rich sequence various computational methods training characterization information mining feature information unlike common peptides logistic regression model throughput computational method curated traditional encoding sorfpp uses catboost identify seps based 2 %- 24 contributive traditional features traditional encoding computational method contributive features driven information encoded peptides attention model xlink "> two models sparsity problem sorfpp outperforms significant roles robust predictions predict seps multiple perspectives long non lncrnas ). including qsorder fused framework enabled us effective models coding rnas art models 5000 /</ 2 pre
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