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已答复Efficient way to cluster points on line y=ax+b? and now extend the idea to higher dimensional data?

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  • 2007年8月17日 17:32Shuvro Mitra答复者用户奖牌用户奖牌用户奖牌用户奖牌用户奖牌
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    Are you using SQL Server Data Mining for clustering?

     

    For points (x,y) in the line y=ax+b, you'll detect clusters only using attribute x since y is a dependent variable. Any clustering algorithm will be able to handle this efficiently. When you mention higher dimensional data, I assume you mean more independent variables, but the idea is the same.

     

    Please let me know any specific questions you have regarding SQL Server Data Mining or Clustering algorithm in general

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  • 2007年8月17日 17:32Shuvro Mitra答复者用户奖牌用户奖牌用户奖牌用户奖牌用户奖牌
     已答复

    Are you using SQL Server Data Mining for clustering?

     

    For points (x,y) in the line y=ax+b, you'll detect clusters only using attribute x since y is a dependent variable. Any clustering algorithm will be able to handle this efficiently. When you mention higher dimensional data, I assume you mean more independent variables, but the idea is the same.

     

    Please let me know any specific questions you have regarding SQL Server Data Mining or Clustering algorithm in general

  • 2009年7月1日 6:17Guennadiy Vanine 用户奖牌用户奖牌用户奖牌用户奖牌用户奖牌
     
    For points (x,y) in the line y=ax+b, you'll detect clusters only using attribute x since y is a dependent variable. Any clustering algorithm will be able to handle this efficiently. When you mention higher dimensional data, I assume you mean more independent variables, but the idea is the same.

    Please let me know any specific questions you have regarding SQL Server Data Mining or Clustering algorithm in general

    Can this be described in more detail?

    I could not grasp who will do what and how. That is - to discern between "you'll detect" and "Any clustering algorithm will be able...".

    Also, I could not understand why "only using attribute x since y is a dependent variable".
    To me, this is quite symmetric:
    x is also dependent on y as x = (y - b) /a


    Guennadi Vanine -- Gennady Vanin -- Геннадий Ванин