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    云南民族大學學報(自然科學版)

    2019, v.28;No.118(06) 576-580+623

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    基于split-and-conquer和非參數向前選擇法的變量選擇
    Non-parametric forward selection method based on split-and-conquer

    李順勇;趙永勝;
    LI Shun-yong;ZHAO Yong-sheng;School of Mathematical Sciences, Shanxi University;

    摘要(Abstract):

    變量選擇是統計學界研究的重要課題之一.當處理高維數據時,一些常用的變量選擇方法大多比較耗時,因此提出了一種既能篩選出高維數據中的變量又能節省時間的方法:基于split-and-conquer的非參數向前選擇法.首先使用split-and-conquer方法將數據進行拆分,然后使用B樣條函數逼近的非參數向前選擇法進行研究.實驗結果表明:基于split-and-conquer的非參數向前選擇法可以較好地將變量選擇出來,并且節省了大量時間.
    Variable selection is one of the important topics in the field of statistics. When dealing with high-dimensional data, most of the commonly used variable selection methods are time-consuming. This paper proposes a method that can filter out the variables in high-dimensional data and save time, that is, the non-parametric forward selection method based on split-and-conquer. Firstly, the split-and-conquer method is used to split the data, and then the non-parametric forward selection method of B-spline function approximation is used. The experimental results show that the non-parametric forward selection method based on split-and-conquer can select variables well, and save a lot of time.

    關鍵詞(KeyWords): 變量選擇;非參數可加性模型;非參數向前選擇法;B樣條函數;線性回歸
    variable selection;non-parametric additive model;non-parametric forward selection;B-spline function;linear regression

    Abstract:

    Keywords:

    基金項目(Foundation): 國家自然科學基金(61573229);; 山西省基礎研究計劃項目(201701D121004);; 山西省回國留學人員科研資助項目(2017-020);; 太原市科技計劃研發項目(2018140105000084)

    作者(Author): 李順勇;趙永勝;
    LI Shun-yong;ZHAO Yong-sheng;School of Mathematical Sciences, Shanxi University;

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    DOI:

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