In a project, we need to deploy a logistic regression model into a production system that only takes SQL scripts as its input. Two functions come in handy, decode() and nvl(). Decode() converts categorical value into a weight and nvl() conveniently replaces null with a desired value. The following SQL scripts is similar to what we delivered.
select transaction_id,
(1/
(1+
exp(-(
nvl(AMT1*.000019199,0)+
nvl(AMT3*(-.00002155),0)+
decode(nvl(substr((TXN_CODE1),1,18),' '),
'XX',-.070935,
'57',-.192319,
'1',-.053794,
'81',-.010813,
'NR',-.079628,
'PD',-.102987,
'P',-1.388433,
'Z6',-.106081,
'01',-1.1528,
'Z4',-.004237,
'T1',.697737,
'AK',-.490381,
'U2',.063712,
'NK',.054354,
'PR',.205336,
'51',-.286213,
'N',.075582,
' ',-.330585,
0)+
decode(nvl(substr( trim(TXN_CODE2),1,18),' '),
'U',-.11176,
0)+
decode(nvl(substr( trim(TXN_CODE3),1,18),' '),
'1',-.642605,
0)+
decode(nvl(substr( trim(TXN_CODE4),1,18),' '),
'00',-.084517,
'10',.057248,
0)
-6.8190776
)
)
)
) as score from tbl_data;
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