metadata
license: mit
tags:
- gender-classification
- advertising
- lightgbm
Gender Prediction Model for Targeted Advertising
Model Description
LightGBM classifier trained on user behavior data to predict gender (Male/Female) for ad targeting. Achieves 82.3% accuracy and 0.817 F1-score.
Features
- User Agent parsing (browser, OS, mobile/tablet)
- Geographic data (country, region, timezone)
- Referer vector components (10-dimensional embedding)
- Time features (hour, weekday, weekend)
Performance
| Metric | Score |
|---|---|
| Accuracy | 0.823 |
| Precision | 0.805 |
| Recall | 0.828 |
| F1-Score | 0.817 |
Usage
import joblib
model = joblib.load('gender_classifier.pkl')
imputer = joblib.load('imputer.pkl')
# Preprocess data using same steps as training
# Then predict