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Feature Mart Data Dictionary:

Demographic

Features like user age and gender.

Feature Name Data Type Definition Android Example iOS Example
gender_prediction integer Predicted gender of the Device. Possible values are “1” for male and “0” for female 0 1
gender_confidence_bucket string Confidence bucket for gender. Value is provided as a 2 character code: [sd (Self declared), hc (High), mc (Medium) & lc (Low)] mc hc
age_bucket_prediction integer Age Bucket of the Device. Value is provided as a 1 digit BucketCode: [1(18-24); 2(25-34); 3(35-44); 4(45-54); 5(55+)] 2 1
age_bucket_confidence_bucket string Confidence bucket for age group. Value is provided as a 2 character code: [sd (Self declared), hc (High), mc (Medium) & lc (Low)] hc hc
predicted_income integer Predicted income bucket of the device where available. High is 3, Average is 2, and Low is 1 2 3

 

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