Conformal prediction for hypersonic flight vehicle classification

Zepu Xi, Xuebin Zhuang, Hongbo Chen
Proceedings of the Eleventh Symposium on Conformal and Probabilistic Prediction with Applications, PMLR 179:118-206, 2022.

Abstract

This paper introduces a probabilistic guaranteed prediction method for trajectory data of the hypersonic flight vehicle classification problem. This paper devoted two problems: (1) hypersonic flight vehicle trajectory classification algorithm using functional data analysis method, and (2) a distributions-free uncertainty quantity for the classification results applying conformal prediction methodology. Our approach provides explicit finite-sample guarantees for any data set by using functional data analysis methods, which map the original data into feature space. The distribution-free uncertainty quantity results for the label of new objects include two indications, such as confidence and credibility respectively. Lastly, the proposed method aims to communicate instance-wise uncertainty under the probabilistic guaranteed and generate a prediction set at a user-specified confidence level for the hypersonic flight vehicle classification problem.

Cite this Paper

BibTeX
@InProceedings{pmlr-v179-xi22a, title = {Conformal prediction for hypersonic flight vehicle classification}, author = {Xi, Zepu and Zhuang, Xuebin and Chen, Hongbo}, booktitle = {Proceedings of the Eleventh Symposium on Conformal and Probabilistic Prediction with Applications}, pages = {118--206}, year = {2022}, editor = {Johansson, Ulf and Boström, Henrik and An Nguyen, Khuong and Luo, Zhiyuan and Carlsson, Lars}, volume = {179}, series = {Proceedings of Machine Learning Research}, month = {24--26 Aug}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v179/xi22a/xi22a.pdf}, url = {https://proceedings.mlr.press/v179/xi22a.html}, abstract = {This paper introduces a probabilistic guaranteed prediction method for trajectory data of the hypersonic flight vehicle classification problem. This paper devoted two problems: (1) hypersonic flight vehicle trajectory classification algorithm using functional data analysis method, and (2) a distributions-free uncertainty quantity for the classification results applying conformal prediction methodology. Our approach provides explicit finite-sample guarantees for any data set by using functional data analysis methods, which map the original data into feature space. The distribution-free uncertainty quantity results for the label of new objects include two indications, such as confidence and credibility respectively. Lastly, the proposed method aims to communicate instance-wise uncertainty under the probabilistic guaranteed and generate a prediction set at a user-specified confidence level for the hypersonic flight vehicle classification problem. } }
Endnote
%0 Conference Paper %T Conformal prediction for hypersonic flight vehicle classification %A Zepu Xi %A Xuebin Zhuang %A Hongbo Chen %B Proceedings of the Eleventh Symposium on Conformal and Probabilistic Prediction with Applications %C Proceedings of Machine Learning Research %D 2022 %E Ulf Johansson %E Henrik Boström %E Khuong An Nguyen %E Zhiyuan Luo %E Lars Carlsson %F pmlr-v179-xi22a %I PMLR %P 118--206 %U https://proceedings.mlr.press/v179/xi22a.html %V 179 %X This paper introduces a probabilistic guaranteed prediction method for trajectory data of the hypersonic flight vehicle classification problem. This paper devoted two problems: (1) hypersonic flight vehicle trajectory classification algorithm using functional data analysis method, and (2) a distributions-free uncertainty quantity for the classification results applying conformal prediction methodology. Our approach provides explicit finite-sample guarantees for any data set by using functional data analysis methods, which map the original data into feature space. The distribution-free uncertainty quantity results for the label of new objects include two indications, such as confidence and credibility respectively. Lastly, the proposed method aims to communicate instance-wise uncertainty under the probabilistic guaranteed and generate a prediction set at a user-specified confidence level for the hypersonic flight vehicle classification problem.
APA
Xi, Z., Zhuang, X. & Chen, H.. (2022). Conformal prediction for hypersonic flight vehicle classification. Proceedings of the Eleventh Symposium on Conformal and Probabilistic Prediction with Applications, in Proceedings of Machine Learning Research 179:118-206 Available from https://proceedings.mlr.press/v179/xi22a.html.

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