Semantic Code Classification for Automated Machine Learning

01/25/2022

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A range of applications for automatic machine learning need the generation process to be controllable. In this work, we propose a way to control the output via a sequence of simple actions, that are called semantic code classes. Finally, we present a semantic code classification task and discuss methods for solving this problem on the Natural Language to Machine Learning (NL2ML) dataset.

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Semantic Code Classification for Automated Machine Learning

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Semantic Code Classification for Automated Machine Learning

Related Research

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Code4ML: a Large-scale Dataset of annotated Machine Learning Code

GPTCloneBench: A comprehensive benchmark of semantic clones and cross-language clones using GPT-3 model and SemanticCloneBench

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