Features like user age and gender.
| Feature Name | Data Type | Definition | Android Example | iOS Example |
| pre_skewness_female | double | Processed value of the device skewness towards gender = female | 0.000414119 | 0 |
| pre_skewness_male | double | Processed value of the device skewness towards gender = male | 0 | 0 |
| 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 |
| pre_skewness_18_24 | double | Processed value of the device skewness towards age group label “18-24” | 0.38536 | 0.02194 |
| pre_skewness_25_34 | double | Processed value of the device skewness towards age group label “25-34” | 0.143 | 0.01521 |
| pre_skewness_35_44 | double | Processed value of the device skewness towards age group label “35-44” | 0.10357 | 0.00786 |
| pre_skewness_45_54 | double | Processed value of the device skewness towards age group label “45-54” | 0.04689 | 0.00255 |
| pre_skewness_55_plus | double | Processed value of the device skewness towards age group label “55+” | 0.01655 | 0.00132 |
| predicted_income | double | Predicted income bucket of the device where available. High is 3, Average is 2, and Low is 1 | 2.0 | 3.0 |
