---
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

```python
import joblib
model = joblib.load('gender_classifier.pkl')
imputer = joblib.load('imputer.pkl')
# Preprocess data using same steps as training
# Then predict
```