Vol 13, No 3

Stellar spectra association rule mining method based on the weighted frequent pattern tree

Jiang-Hui Cai, Xu-Jun Zhao, Shi-Wei Sun, Ji-Fu Zhang, Hai-Feng Yang


Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced, and the weight of a single property in the stellar spectrum is determined by information entropy. On that basis, a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree. Important properties of the spectral line are highlighted using this method. At the same time, the waveform of the whole spectrum is taken into account. The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.


methods: data analysis — stars: fundamental parameters — techniques: spectroscopic — astronomical data bases: miscellaneous

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