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README.md

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 ---
 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
+```

gender_classifier.pkl

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+oid sha256:834581ceabf8e62c88b1daa8583e164c3d516965d8668968a13881e339e745bf
+size 3483364

imputer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a33d01b5f7d4fbc7c959de5eb02cabda1da1f3c5c3557124654bdb2492299f06
+size 1215