.png){kind=icon}
返回
Bayesian model selection for mining mass spectrometry data
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neunet.2005.06.046.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A procedure for learning a probabilistic model from mass spectrometry data that accounts for domain specific noise and mitigates the complexity of Bayesian structure learning is presented. We evaluate the algorithm by applying the learned probabilistic model to microorganism detection from mass spectrometry data. (c) 2005 Published by Elsevier Ltd.
Keyword:
Bayesian networks
structure learning
domain knowledge
model selection
mass spectrometry
microorganism detection
biomarker
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.3
论文数:
7.8K
被引数:
3.0W
机构
暂无机构信息
.png){kind=icon}
