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我们正在考虑开始使用kxen来构建客户数据的逻辑回归模型。我们迄今为止一直使用SAS和R工作室,并且我很难清楚地了解Kxen中使用的K2R软件包的逻辑。KXEN的回归系数
1)如果我想在sql中构建评分函数,如何从Kxen - (beta, intercept)
获得回归系数?
得到下面的SQL代码输出(封闭的代码部分):
SELECT $key, $target_variable, CAST((CASE
WHEN $target_variable <= -1.32354053933e0 THEN 0.0e0
WHEN $target_variable <= -3.245405264555e-1 THEN 0.0e0
WHEN $target_variable <= -3.235405393301e-1 THEN (2.283134417281e-3*$target_variable+7.409696685844e-4)
WHEN $target_variable <= -2.673812457267e-1 THEN (4.065409082516e-5*$target_variable+1.543635190092e-5)
WHEN $target_variable <= -"2.673250302176e-1 THEN (4.057282329758e1*"$target_variable"+1.084841700789e1)
..... [more code here]
ELSE 0.0e0
END) AS FLOAT)
AS PROBA0
into [table_name]
FROM
(
SELECT $key, (2.191922889118e-2 + CAST((CASE
WHEN ("predictor1" IS NULL OR "predictor1" = '' ) THEN -6.39011247354e-3
WHEN "predictor1" <= -2.432307283e0 THEN -1.541583426389e-1
WHEN "predictor1" <= 9.41313103e-1 THEN (9.932069236689e-2*"predictor1"+8.742010175092e-2)
WHEN "predictor1" <= 1.696595422e0 THEN (4.169961790129e-2*"predictor1""+2.454336172985e-1)
WHEN "predictor1" >= 1.696595402e0 THEN 3.16180997712e-1
ELSE -6.39011247354e-3
END) AS FLOAT)+
CAST((CASE
WHEN ("predictor2" IS NULL OR "predictor2" = '' ) THEN 3.937894402762e-3
WHEN "predictor2" <= -9.99550198e-1 THEN -2.797353866946e-2
WHEN "predictor2" <= -1.27770581e-1 THEN (2.918798485695e-2*"predictor2""+1.201317665409e-3)
WHEN "predictor2" <= 3.78487285e-1 THEN (2.547969219572e-2*"predictor2"+6.997428207111e-3)
...... [more code here]
) AS $target_varialbe FROM [table_name]
) TMPTABLE0
预测都inputed WOE变换后并定义为连续变量。
2)当按订单分配订单的客户时,订单是不同的,那么当按概率排序时 - 从分数到概率的转换不是单调的函数?我的目标是为客户分配标准化的分数/概率。
任何人都可以解释一下吗?