https://github.com/omara32/house-price-prediction-using-sklearn

House price prediction using sklearn's linear regression model
https://github.com/omara32/house-price-prediction-using-sklearn

house-price-prediction linear-regression python regression sklearn visualization

Last synced: 6 months ago
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House price prediction using sklearn's linear regression model

• Host: GitHub
• URL: https://github.com/omara32/house-price-prediction-using-sklearn
• Owner: OmarA32
• Created: 2025-04-05T04:35:29.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-04-05T04:54:47.000Z (6 months ago)
• Last Synced: 2025-04-09T19:17:17.886Z (6 months ago)
• Topics: house-price-prediction, linear-regression, python, regression, sklearn, visualization
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Housing Price Prediction with scikit-learn

This project demonstrates the use of **scikit-learn** for building a linear regression model to predict housing prices. The dataset is preprocessed by detecting and removing outliers using the Interquartile Range (IQR) method. After the outliers are removed, the model’s performance is evaluated using common regression metrics.

## Features:

- **Outlier Detection**

- **Data Preprocessing**:

- **Model Training**

- **Model Evaluation**:

  - Mean Squared Error (MSE)

  - Mean Absolute Error (MAE)

  - R-squared (R²)

- **Visualization**:

  - Scatter plot of predicted vs. actual sale prices.

  - Box plots showing the distribution of features after outlier removal.

## Dependencies:

- `pandas`

- `numpy`

- `scikit-learn`

- `seaborn`

- `matplotlib`

Database Used: House Prices from Kaggle.