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--- |
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tags: |
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- regression |
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- house-prices |
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license: mit |
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model_name: House Price Prediction |
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library_name: joblib |
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language: |
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- en |
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--- |
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# House Price Prediction Model 🏠 |
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**📌 Introduction** |
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This machine learning model predicts house prices using linear regression. It estimates prices based on input features like square footage, number of bedrooms, and location. |
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This dataset includes 1,000 homes, with the following features : |
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- **Size**: The size of the house |
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- **Bedrooms**: The number of bedrooms in the house |
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- **Bathrooms**: The number of bathrooms in the house |
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- **Location**: A feature representing the location of the house |
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- **YearBuilt**: The year the house was built |
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- **RoofType**: The type of roof on the house |
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- **Price**: The price of the house |
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The goal is to understand how these factors influence a home’s value. |
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**🚀 How to Use the Model** |
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```python |
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from huggingface_hub import hf_hub_download |
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import joblib |
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model_path = hf_hub_download( |
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repo_id="sumeeh/house-price-prediction-LinearRegression", |
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filename="House_Price_Prediction_LinearRegression.pkl" |
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) |
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model = joblib.load(model_path) |
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``` |
