用简单DNN预测精油化学成分与性质关系
A simple DNN regression for the chemical composition in essential oil
- 构建三个简单DNN回归模型，基于化学成分预测精油性质
- 在小样本数据下仍有效训练，但存在过拟合现象
- 适合做精油成分分析的快速建模参考
尽管单分子活性/性质的实验设计和方法研究已广泛开展，但针对化学成分的研究却较少，仅有少数前期工作涉及。本研究配置了三个简单的DNN回归模型，基于化学成分预测精油性质。尽管由于数据集规模较小导致模型出现过拟合，但所有模型均成功训练。该方法为精油成分与性质关联提供了轻量级建模思路。
原文摘要 · Abstract (English)
Although experimental design and methodological surveys for mono-molecular activity/property has been extensively investigated, those for chemical composition have received little attention, with the exception of a few prior studies. In this study, we configured three simple DNN regressors to predict essential oil property based on chemical composition. Despite showing overfitting due to the small size of dataset, all models were trained effectively in this study.
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