tf-idf numeric 0
Semantic Code Classification for Automated Machine Learning
Guseva, Polina, Drozdova, Anastasia, Denisenko, Natalia, Sapozhnikova, Daria, Pyaternev, Ivan, Scherbakova, Anna, Ustuzhanin, Andrey
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.