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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 trained to predict air quality categories based on air quality index (AQI) values. The model takes AQI values of individual pollutants as input and predicts the overall air quality category, such as 'good', 'moderate', 'unhealthy', etc.
Dataset The model was trained using the Global Air Pollution Dataset available on Kaggle. The dataset contains air quality data from various cities and countries, including AQI values for different pollutants.
Dataset Shape: (23035, 12) Model Performance Accuracy: 99.91% Classification Report: yaml Copy code 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
macro avg 0.99 0.99 0.99 4607 weighted avg 1.00 1.00 1.00 4607 Usage To use the model:
Install the required dependencies. Load the trained model (hackathonrf.joblib). Provide AQI values of individual pollutants as input. Obtain the predicted air quality category. Dependencies scikit-learn pandas numpy requests Author This model was developed by [Your Name].