- author = "Wenqiang Zhang and Peng Ge and Weidong Jin and Jian Guo",
- title = "Radar Signal Recognition Based on {TPOT} and {LIME}",
- booktitle = "2018 37th Chinese Control Conference (CCC)",
- year = "2018",
- pages = "4158--4163",
- month = "25-27 " # jul,
- keywords = "genetic algorithms, genetic programming, TPOT",
- isbn13 = "978-1-5386-4968-8",
- ISSN = "1934-1768",
-
DOI = "
doi:10.23919/ChiCC.2018.8483165",
- abstract = "Aiming at solving the existing problems of radar signal recognition methods, this paper presents a method based on Tree-based Pipeline Optimization Tool (TPOT) and Local Interpretable Model-agnostic Explanations (LIME). This method uses genetic programming based on the tree structure to generate the machine learning pipeline. The structure and parameters are evolved to obtain the optimal performance of the machine learning pipeline. Then the prediction results are interpreted by the interpreter to evaluate whether the model is available. When there are multiple signals with similar interpretative properties, it shows that these signals are indistinguishable. The prediction results are interpreted on this model which was re-trained for indistinguishable signals to validate the validity of the LIME interpreter. The experimental results show that the proposed method can not only optimize the machine learning pipeline for different data sets, but also determine the type of indistinguishable radar signal in the data set according to the interpretability.",
-
notes = "School of Electrical Engineering, Southwest Jiaotong
University, Chengdu, 611756, P. R. China
Also known as \cite{8483165}",
