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college-admit-predictor
Piyush090805/college-admit-predictor
college-admit-predictor is a machine learning model from Piyush090805. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model predicts college admission chances based on GRE, TOEFL, CGPA, SOP, LOR, University Rating, and Research Experience. Trained on a synthetic + processed dataset, optimized to achieve ~97% accuracy.
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Updated Sep 21, 2025
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At a glance
- Access
- Public
- Created
- Sep 21, 2025
- Updated
- Sep 21, 2025
- SHA
- fea8fd94
Model card
From the Hugging Face model README
🎓 College Admission Predictor (RandomForest)
This model predicts college admission chances based on GRE, TOEFL, CGPA, SOP, LOR, University Rating, and Research Experience.
Trained on a synthetic + processed dataset, optimized to achieve ~97% accuracy.
📊 Results
| Metric | Score |
|---|---|
| Accuracy | 97% |
| Precision | 0.93 |
| Recall | 0.92 |
Confusion Matrix
📂 Files in this repo
rf_best_test_clean.pkl→ Trained RandomForest modeltest_clean_with_label.csv→ Processed dataset with labelsREADME.md→ Model cardLICENSE→ Apache 2.0 License
🚀 How to Use
from huggingface_hub import hf_hub_download
import joblib
import pandas as pd
# Download model
model_path = hf_hub_download(repo_id="your-username/college-admit-predictor", filename="rf_best_test_clean.pkl")
# Load model
model = joblib.load(model_path)
# Example prediction
sample = pd.DataFrame([{
"gre": 325, "toefl": 112, "uni_rating": 4,
"sop": 4.5, "lor": 4.0, "cgpa": 9.0, "research": 1,
"academic_score": 2.5, "gre_toefl": 36400, "cgpa_times_rating": 36.0
}])
print(model.predict(sample))
- Created
- Sep 21, 2025
- Updated
- Sep 21, 2025