覃文忠, 王建梅, 刘妙龙. 混合地理加权回归模型算法研究[J]. 武汉大学学报 ( 信息科学版), 2007, 32(2): 115-119.
引用本文: 覃文忠, 王建梅, 刘妙龙. 混合地理加权回归模型算法研究[J]. 武汉大学学报 ( 信息科学版), 2007, 32(2): 115-119.
MA Ronghua, HE Zengyou, . Mining Complete and Correct Frequent Neighboring Class Sets from Spatial Databases[J]. Geomatics and Information Science of Wuhan University, 2007, 32(2): 115-119.
Citation: MA Ronghua, HE Zengyou, . Mining Complete and Correct Frequent Neighboring Class Sets from Spatial Databases[J]. Geomatics and Information Science of Wuhan University, 2007, 32(2): 115-119.

混合地理加权回归模型算法研究

Mining Complete and Correct Frequent Neighboring Class Sets from Spatial Databases

  • 摘要: 以迭代算法为基础,推导出混合地理加权回归模型的常系数(全局参数)和变系数(局域参数)的计算方法,并以上海市住宅小区楼盘销售平均价格为例进行验证。结果表明,混合地理加权回归模型的计算量略大于地理加权回归模型,但对样本数据的拟合更好,局域参数估计更稳健。

     

    Abstract: A recent work has introduced the problem of mining neighboring class sets,where instances of each class of a neighboring class set are grouped using their Euclidean distances from each other.Although the concept of neighboring class sets is a useful one,the effective computation of frequent neighboring class sets is only partially solved.A novel algorithm for mining frequent neighboring class sets from spatial datasets is presented.Compared to the previous algorithm,the algorithm can discover complete and correct frequent neighboring class sets.

     

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