Spatial cone object classification based on improved naive Bayes algorithm

Guanjie Chen; Caiyun Wang; Yida Wu; Huiwen Zhang

doi:10.1117/12.3014491

8 December 2023 Spatial cone object classification based on improved naive Bayes algorithm

Guanjie Chen, Caiyun Wang, Yida Wu, Huiwen Zhang

Proceedings Volume 12943, International Workshop on Signal Processing and Machine Learning (WSPML 2023); 129430F (2023) https://doi.org/10.1117/12.3014491
Event: International Workshop on Signal Processing and Machine Learning (WSPML 2023), 2023, Hangzhou, ZJ, China

Abstract

In order to solve the problems of low recognition accuracy of traditional classifiers due to multiple penetration measures and difficulty in identifying cone targets, an improved instance weighted naive Bayes (IWNB) classifier based on classification fuzzy regions is proposed. Firstly, the classifier constructs a naive Bayes classifier based on the training set data, and then makes full use of data information to improve the classification accuracy by the lazy instance weighting. Secondly, the training set data is used to test the performance of the classifier, and the classification fuzzy region is established by collecting the samples which are not classified correctly. Then the feature is screened by means of sorting the importance of them through the dispersion of the universe to achieve the effect of data dimensionality reduction. The samples in the test set are firstly recognized by the classifier. For the samples in the fuzzy region, the K-nearest neighbour classifier is employed for secondary target classification to get the final result. The experimental results show that the algorithm can effectively improve the classification effect of different targets in the ballistic midcourse and has good robustness, and also has high accuracy under the condition of small sample size, at the same time, has good performance under different data sets.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guanjie Chen, Caiyun Wang, Yida Wu, and Huiwen Zhang "Spatial cone object classification based on improved naive Bayes algorithm", Proc. SPIE 12943, International Workshop on Signal Processing and Machine Learning (WSPML 2023), 129430F (8 December 2023); https://doi.org/10.1117/12.3014491

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KEYWORDS

Detection and tracking algorithms

Education and training

Target recognition

Fuzzy logic

Radar

Feature extraction

Principal component analysis

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