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Updated: Jun 24, 2025

An R-Based Landscape Validation of a Competing Risk Model
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预测宫癌风险概率使用先进的H20AutoML和局部可解释模型-不可知解释技术

Sashikanta Prusty1, Srikanta Patnaik2, Sujit Kumar Dash3

  • 1Department of Computer Science and Engineering, Siksha O Anusandhan University Institute of Technical Education and Research, Bhubaneswar, Odisha, India.

PeerJ. Computer science
|June 10, 2024
PubMed
概括

这项研究介绍了H2O AutoML与局部可解释模型-不可知解释 (LIME) 进行增强的宫癌预测. 这种新的方法自动化了机器学习 (ML) 模型训练,减少了人类的努力,提高了癌症检测的准确性.

关键词:
在AutoML中使用AutoML.宫癌数据集的数据在H2O.ai.ai中.在 LIME 时代,绩效指标是指性能指标.

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