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| title: HCC CSA April24 Hackathon | |
| emoji: 🌍 | |
| colorFrom: pink | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 4.28.3 | |
| app_file: app.py | |
| pinned: false | |
| # Air Quality Prediction Model | |
| This repository contains a machine learning model for predicting air quality based on AQI (Air Quality Index) values of various pollutants. The model is trained on a dataset sourced from Kaggle's Global Air Pollution Dataset. | |
| ## Dataset | |
| - **Dataset Name**: Global Air Pollution Dataset | |
| - **Dataset Source**: [Kaggle](https://www.kaggle.com/datasets/hasibalmuzdadid/global-air-pollution-dataset/) | |
| - **Dataset Size**: 23,463 rows, 12 columns | |
| ## Model Performance | |
| - **Model Name**: hackathonrf.joblib | |
| - **Accuracy**: 99.91% | |
| - **Classification Report**: | |
| precision recall f1-score support | |
| 0 1.00 1.00 1.00 1926 | |
| 1 1.00 0.91 0.95 45 | |
| 2 1.00 1.00 1.00 1841 | |
| 3 1.00 1.00 1.00 405 | |
| 4 1.00 1.00 1.00 333 | |
| 5 0.93 1.00 0.97 57 | |
| accuracy 1.00 4607 | |