I'm performing a Logistic regression for a binary classification task.
As a preprocessing technique I use a transformation with WOE and Information value(IV), but I found something counterintuitive since when I check the regression's coefficients there are some that have the value of zero though those variables have a "high" IV
From the table below I see that for variable CANT_ACT_ECONOMICAS has a coefficient of 0 but is has the highest IV
Model coefficients: ***** Fature Impportance ***** importance COMPANY_DOMAIN_CLASS 0.027879 GENDER 0.000000 CANT_ACT_ECONOMICAS 0.000000 ACT_ECONOMIC_GROUP -0.065918 PRODUCTIVE_ZONE -0.108427 DOMAIN -0.284159 COMPANY_AGE -0.321768 WEEKDAY -0.474630 ACT_ECONOMIC_RISK -0.595959 USE_OF_PROCEEDS_INTENT -0.805546 AGE -0.895112 USE_OF_PROCEEDS_RISK -0.898074 START_HOUR -1.030490 Information Value: AVG_IV CANT_ACT_ECONOMICAS 0.058573 COMPANY_AGE 0.034645 PRODUCTIVE_ZONE 0.032958 ACT_ECONOMIC_RISK 0.030869 COMPANY_DOMAIN_CLASS 0.019605 AGE 0.004793 USE_OF_PROCEEDS_RISK 0.004689 USE_OF_PROCEEDS_INTENT 0.003318 START_HOUR 0.001870 WEEKDAY 0.001217 DOMAIN 0.001032 GENDER 0.000568 ACT_ECONOMIC_GROUP NaN
My question is:
If a variable have a high information value, does it necessarily have to have high importance on logistic regression model (high coefficient)?