Conformal prediction for hypersonic flight vehicle classification

Zepu Xi, Xuebin Zhuang, Hongbo Chen

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.

External IDs:dblp:conf/copa/XiZC22