在生物工程文本语料库中验证机器学习应用的IDE支持

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2022-12-06 DOI:10.1109/BIBM55620.2022.9995298

Piyush Basia, Tae-Hyuk Ahn, Myoungkyu Song

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引用次数: 0

摘要

在实践中，机器学习建模对软件系统至关重要。ML应用程序需要验证其模型和实现，但质量验证对于开发人员来说是一个具有挑战性且耗时的过程。为了解决这一限制，我们提出了一种新的ML应用验证技术，以帮助开发人员或研究人员(例如，生物工程领域)检查(1)软件代码(ML API用法)和(2)ML模型(提取的特征)。

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An IDE Support for Validating Machine Learning Applications in Bioengineering Text Corpora

Modeling in machine learning (ML) is critical for software systems in practice. ML applications are required to validate their models and implementations but quality validation is a challenging and time-consuming process for developers. To address this limitation, we present a novel validation technique for ML applications to help developers or researchers (e.g., bioengineering domain) inspect (1) software code (ML API usages) and (2) ML model (extracted features).

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来源期刊

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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