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    3/22/2007

    几个有名的数据挖掘与机器学习的练习数据集(一)

    都是公开数据集,都能从网上得到。一些来自软件的自带数据集,一些来自网上的公开数据集,还有一些就是从论文中直接复制过来。我的想法是好东西应该多多覆盖,不嫌重复。

    第一个来自Witten的《数据挖掘:实用机器学习技术》的隐性眼镜数据(the Contact Lens data),以下的数据你Copy过去,保存数据格式为.txt,就是一个带逗号分割的文本文件啦,可以直接用Excel打开(下面的东西本来就是把Excel文件保存为带逗号分割的文本文件):

    /*隐性眼镜数据集(the Contact Lens data),这组数据是验光师根据每个病人的情况作出到底使用哪种隐性眼镜的诊断。其中5个变量,
    1.Age:年龄,分为老年( Presbyopic,老花眼 )、中年(Pre-presbyopic)和青年(Young);
    2.SpectaclePrescription:就是Spectacle Prescription,视力诊断,取值有近视(Myope)和远视(Hypermetrope);
    3.Astigmatism,是否散光;
    4.TearProductionRate,Tear Production Rate,泪流量,取值为正常(Normal)和缺乏(Reduced);
    5.最后是推荐的镜片,RecommendedLenses,Recommended Lenses,软的、硬的或者不能佩戴隐性眼镜。*/

    Age , SpectaclePrescription , Astigmatism , TearProductionRate , RecommendedLenses
    Young , Myope , No , Reduced , None
    Young , Myope , No , Normal , Soft
    Young , Myope , Yes , Reduced , None
    Young , Myope , Yes , Normal , Hard
    Young , Hypermetrope , No , Reduced , None
    Young , Hypermetrope , No , Normal , Soft
    Young , Hypermetrope , Yes , Reduced , None
    Young , Hypermetrope , Yes , Normal , hard
    Pre-presbyopic , Myope , No , Reduced , None
    Pre-presbyopic , Myope , No , Normal , Soft
    Pre-presbyopic , Myope , Yes , Reduced , None
    Pre-presbyopic , Myope , Yes , Normal , Hard
    Pre-presbyopic , Hypermetrope , No , Reduced , None
    Pre-presbyopic , Hypermetrope , No , Normal , Soft
    Pre-presbyopic , Hypermetrope , Yes , Reduced , None
    Pre-presbyopic , Hypermetrope , Yes , Normal , None
    Presbyopic , Myope , No , Reduced , None
    Presbyopic , Myope , No , Normal , None
    Presbyopic , Myope , Yes , Reduced , None
    Presbyopic , Myope , Yes , Normal , Hard
    Presbyopic , Hypermetrope , No , Reduced , None
    Presbyopic , Hypermetrope , No , Normal , Soft
    Presbyopic , Hypermetrope , Yes , Reduced , None
    Presbyopic , Hypermetrope , Yes , Normal , None

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