Spark2 ML包，机器学习示例数据Affairs

// affairs：一年来婚外情的频率   
// gender：性别   
// age：年龄   
// yearsmarried：婚龄   
// children：是否有小孩   
// religiousness：宗教信仰程度（5分制，1分表示反对，5分表示非常信仰）  
// education：学历  
// occupation：职业（逆向编号的戈登7种分类）   
// rating：对婚姻的自我评分（5分制，1表示非常不幸福，5表示非常幸福）  


val dataList: List[(Double, String, Double, Double, String, Double, Double, Double, Double)] = List( 
      (0, "male", 37, 10, "no", 3, 18, 7, 4), 
      (0, "female", 27, 4, "no", 4, 14, 6, 4), 
      (0, "female", 32, 15, "yes", 1, 12, 1, 4), 
      (0, "male", 57, 15, "yes", 5, 18, 6, 5), 
      (0, "male", 22, 0.75, "no", 2, 17, 6, 3), 
      (0, "female", 32, 1.5, "no", 2, 17, 5, 5), 
      (0, "female", 22, 0.75, "no", 2, 12, 1, 3), 
      (0, "male", 57, 15, "yes", 2, 14, 4, 4), 
      (0, "female", 32, 15, "yes", 4, 16, 1, 2), 
      (0, "male", 22, 1.5, "no", 4, 14, 4, 5), 
      (0, "male", 37, 15, "yes", 2, 20, 7, 2), 
      (0, "male", 27, 4, "yes", 4, 18, 6, 4), 
      (0, "male", 47, 15, "yes", 5, 17, 6, 4), 
      (0, "female", 22, 1.5, "no", 2, 17, 5, 4), 
      (0, "female", 27, 4, "no", 4, 14, 5, 4), 
      (0, "female", 37, 15, "yes", 1, 17, 5, 5), 
      (0, "female", 37, 15, "yes", 2, 18, 4, 3), 
      (0, "female", 22, 0.75, "no", 3, 16, 5, 4), 
      (0, "female", 22, 1.5, "no", 2, 16, 5, 5), 
      (0, "female", 27, 10, "yes", 2, 14, 1, 5), 
      (0, "female", 22, 1.5, "no", 2, 16, 5, 5), 
      (0, "female", 22, 1.5, "no", 2, 16, 5, 5), 
      (0, "female", 27, 10, "yes", 4, 16, 5, 4), 
      (0, "female", 32, 10, "yes", 3, 14, 1, 5), 
      (0, "male", 37, 4, "yes", 2, 20, 6, 4), 
      (0, "female", 22, 1.5, "no", 2, 18, 5, 5), 
      (0, "female", 27, 7, "no", 4, 16, 1, 5), 
      (0, "male", 42, 15, "yes", 5, 20, 6, 4), 
      (0, "male", 27, 4, "yes", 3, 16, 5, 5), 
      (0, "female", 27, 4, "yes", 3, 17, 5, 4), 
      (0, "male", 42, 15, "yes", 4, 20, 6, 3), 
      (0, "female", 22, 1.5, "no", 3, 16, 5, 5), 
      (0, "male", 27, 0.417, "no", 4, 17, 6, 4), 
      (0, "female", 42, 15, "yes", 5, 14, 5, 4), 
      (0, "male", 32, 4, "yes", 1, 18, 6, 4), 
      (0, "female", 22, 1.5, "no", 4, 16, 5, 3), 
      (0, "female", 42, 15, "yes", 3, 12, 1, 4), 
      (0, "female", 22, 4, "no", 4, 17, 5, 5), 
      (0, "male", 22, 1.5, "yes", 1, 14, 3, 5), 
      (0, "female", 22, 0.75, "no", 3, 16, 1, 5), 
      (0, "male", 32, 10, "yes", 5, 20, 6, 5), 
      (0, "male", 52, 15, "yes", 5, 18, 6, 3), 
      (0, "female", 22, 0.417, "no", 5, 14, 1, 4), 
      (0, "female", 27, 4, "yes", 2, 18, 6, 1), 
      (0, "female", 32, 7, "yes", 5, 17, 5, 3), 
      (0, "male", 22, 4, "no", 3, 16, 5, 5), 
      (0, "female", 27, 7, "yes", 4, 18, 6, 5), 
      (0, "female", 42, 15, "yes", 2, 18, 5, 4), 
      (0, "male", 27, 1.5, "yes", 4, 16, 3, 5), 
      (0, "male", 42, 15, "yes", 2, 20, 6, 4), 
      (0, "female", 22, 0.75, "no", 5, 14, 3, 5), 
      (0, "male", 32, 7, "yes", 2, 20, 6, 4), 
      (0, "male", 27, 4, "yes", 5, 20, 6, 5), 
      (0, "male", 27, 10, "yes", 4, 20, 6, 4), 
      (0, "male", 22, 4, "no", 1, 18, 5, 5), 
      (0, "female", 37, 15, "yes", 4, 14, 3, 1), 
      (0, "male", 22, 1.5, "yes", 5, 16, 4, 4), 
      (0, "female", 37, 15, "yes", 4, 17, 1, 5), 
      (0, "female", 27, 0.75, "no", 4, 17, 5, 4), 
      (0, "male", 32, 10, "yes", 4, 20, 6, 4), 
      (0, "female", 47, 15, "yes", 5, 14, 7, 2), 
      (0, "male", 37, 10, "yes", 3, 20, 6, 4), 
      (0, "female", 22, 0.75, "no", 2, 16, 5, 5), 
      (0, "male", 27, 4, "no", 2, 18, 4, 5), 
      (0, "male", 32, 7, "no", 4, 20, 6, 4), 
      (0, "male", 42, 15, "yes", 2, 17, 3, 5), 
      (0, "male", 37, 10, "yes", 4, 20, 6, 4), 
      (0, "female", 47, 15, "yes", 3, 17, 6, 5), 
      (0, "female", 22, 1.5, "no", 5, 16, 5, 5), 
      (0, "female", 27, 1.5, "no", 2, 16, 6, 4), 
      (0, "female", 27, 4, "no", 3, 17, 5, 5), 
      (0, "female", 32, 10, "yes", 5, 14, 4, 5), 
      (0, "female", 22, 0.125, "no", 2, 12, 5, 5), 
      (0, "male", 47, 15, "yes", 4, 14, 4, 3), 
      (0, "male", 32, 15, "yes", 1, 14, 5, 5), 
      (0, "male", 27, 7, "yes", 4, 16, 5, 5), 
      (0, "female", 22, 1.5, "yes", 3, 16, 5, 5), 
      (0, "male", 27, 4, "yes", 3, 17, 6, 5), 
      (0, "female", 22, 1.5, "no", 3, 16, 5, 5), 
      (0, "male", 57, 15, "yes", 2, 14, 7, 2), 
      (0, "male", 17.5, 1.5, "yes", 3, 18, 6, 5), 
      (0, "male", 57, 15, "yes", 4, 20, 6, 5), 
      (0, "female", 22, 0.75, "no", 2, 16, 3, 4), 
      (0, "male", 42, 4, "no", 4, 17, 3, 3), 
      (0, "female", 22, 1.5, "yes", 4, 12, 1, 5), 
      (0, "female", 22, 0.417, "no", 1, 17, 6, 4), 
      (0, "female", 32, 15, "yes", 4, 17, 5, 5), 
      (0, "female", 27, 1.5, "no", 3, 18, 5, 2), 
      (0, "female", 22, 1.5, "yes", 3, 14, 1, 5), 
      (0, "female", 37, 15, "yes", 3, 14, 1, 4), 
      (0, "female", 32, 15, "yes", 4, 14, 3, 4), 
      (0, "male", 37, 10, "yes", 2, 14, 5, 3), 
      (0, "male", 37, 10, "yes", 4, 16, 5, 4), 
      (0, "male", 57, 15, "yes", 5, 20, 5, 3), 
      (0, "male", 27, 0.417, "no", 1, 16, 3, 4), 
      (0, "female", 42, 15, "yes", 5, 14, 1, 5), 
      (0, "male", 57, 15, "yes", 3, 16, 6, 1), 
      (0, "male", 37, 10, "yes", 1, 16, 6, 4), 
      (0, "male", 37, 15, "yes", 3, 17, 5, 5), 
      (0, "male", 37, 15, "yes", 4, 20, 6, 5), 
      (0, "female", 27, 10, "yes", 5, 14, 1, 5), 
      (0, "male", 37, 10, "yes", 2, 18, 6, 4), 
      (0, "female", 22, 0.125, "no", 4, 12, 4, 5), 
      (0, "male", 57, 15, "yes", 5, 20, 6, 5), 
      (0, "female", 37, 15, "yes", 4, 18, 6, 4), 
      (0, "male", 22, 4, "yes", 4, 14, 6, 4), 
      (0, "male", 27, 7, "yes", 4, 18, 5, 4), 
      (0, "male", 57, 15, "yes", 4, 20, 5, 4), 
      (0, "male", 32, 15, "yes", 3, 14, 6, 3), 
      (0, "female", 22, 1.5, "no", 2, 14, 5, 4), 
      (0, "female", 32, 7, "yes", 4, 17, 1, 5), 
      (0, "female", 37, 15, "yes", 4, 17, 6, 5), 
      (0, "female", 32, 1.5, "no", 5, 18, 5, 5), 
      (0, "male", 42, 10, "yes", 5, 20, 7, 4), 
      (0, "female", 27, 7, "no", 3, 16, 5, 4), 
      (0, "male", 37, 15, "no", 4, 20, 6, 5), 
      (0, "male", 37, 15, "yes", 4, 14, 3, 2), 
      (0, "male", 32, 10, "no", 5, 18, 6, 4), 
      (0, "female", 22, 0.75, "no", 4, 16, 1, 5), 
      (0, "