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WOE & IV
WOE (Weight of Evidence) determines the predictive power of an independent variable in relation to the dependent variable.
WOE = ln (%non events/%events)
The independent variables is replaced by WOE - It is monotonic and continuous
#DataScience #WOE #IV
1/n
WOE (Weight of Evidence) determines the predictive power of an independent variable in relation to the dependent variable.
WOE = ln (%non events/%events)
The independent variables is replaced by WOE - It is monotonic and continuous
#DataScience #WOE #IV
1/n
Steps-
1 - For Continous Variables Make Bins of the Data
2 - Min 5% Data in each bin and non zero events/non-events in each bin
3 - Missings to be grouped separately
4 - Use the WOE formula
5 - Regroup similar value bins.
WOE is monotonic
2/n
1 - For Continous Variables Make Bins of the Data
2 - Min 5% Data in each bin and non zero events/non-events in each bin
3 - Missings to be grouped separately
4 - Use the WOE formula
5 - Regroup similar value bins.
WOE is monotonic
2/n
Benefits-
1 - Treats Outliers
2 - Missing Values are binned separately
3 - Dummy Encoding is not required
4 - Strict Linear relation of the WOE Values
3/n
1 - Treats Outliers
2 - Missing Values are binned separately
3 - Dummy Encoding is not required
4 - Strict Linear relation of the WOE Values
3/n
