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Weighting Features Before Applying Machine Learning Methods to Pulsar Search

Abstract : In recent years, different Artificial Intelligence methods have been applied to pulsar search, such as Artificial Neural Network method, PEACE Sorting Algorithm, Real-time Classification method. In this paper, Weighting Feature method before applying machine learning (ML) was proposed. We give weight to each feature according to its ability to distinguish pulsar and non-pulsar candidates. The ability is determined by the separation degree of the distribution of pulsars and non-pulsars on particular feature. And then use the ML methods to classify different types of candidates. The results show that this method is significant. The accuracy of identifying pulsars and modeling time were both improved after weighting.
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Dayang Wang, Qian Yin, Hongfeng Wang. Weighting Features Before Applying Machine Learning Methods to Pulsar Search. 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.241-247, ⟨10.1007/978-3-319-68121-4_26⟩. ⟨hal-01820903⟩

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