Systems Engineering and Electronics ›› 2021, Vol. 43 ›› Issue (7): 2011-2020.doi: 10.12305/j.issn.1001-506X.2021.07.34

• Reliability • Previous Articles    

Recommendation method for avionics feature selection algorithm basedon meta-learning

Ruifeng LI, Aiqiang XU*, Weichao SUN, Shuyou WANG   

  1. Naval Aviation University, Yantai 264001, China
  • Received:2020-07-14 Online:2021-06-30 Published:2021-07-08
  • Contact: Aiqiang XU

Abstract:

In order to reduce the test data of avionics effectively and remove redundant information and irrelevant features, based on the existing feature selection algorithms in the field of machine learning, a recommendation method for avionics feature selection algorithm under the meta-learning framework is proposed. The proposed method aims to recommend appropriate feature selection algorithms according to the information contained in the test data of different avionics. Firstly, the description method of data set feature is analyzed. Then, the algorithm performance evaluation method based on the multi-metric index is introduced. Finally, the framework of recommendation method for feature selection algorithm is given. A metadata database is established on 42 avionics data sets and 13 filtering feature selection algorithms, the leave-one-out method is used for cross validation. The recommended hit radio reaches more than 90% and the recommended performance radio reaches more than 97%.

Key words: fault diagnosis, meta-learning, feature selection, algorithm recommendation, avionics

CLC Number: 

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