Jupyter Notebook

https://nbviewer.org/github/RoseWrightdev/AirQuality-Classification-Model/blob/main/main.ipynb

Air Quality and Pollution Assessment Classification Model

Key features of the dataset

• Temperature (°C): Average temperature of the region.

• Humidity (%): Relative humidity recorded in the region.

• PM2.5 Concentration (µg/m³): Fine particulate matter levels.

• PM10 Concentration (µg/m³): Coarse particulate matter levels.

• NO2 Concentration (ppb): Nitrogen dioxide levels.

• SO2 Concentration (ppb): Sulfur dioxide levels.

• CO Concentration (ppm): Carbon monoxide levels.

• Proximity to Industrial Areas (km): Distance to the nearest industrial zone.

• Population Density (people/km²): Number of people per square kilometer in the region.

Target Variable: Air Quality Levels

• Good: Clean air with low pollution levels.

• Moderate: Acceptable air quality but with some pollutants present.

• Poor: Noticeable pollution that may cause health issues for sensitive groups.

• Hazardous: Highly polluted air poses serious health risks to the population.

Dataset

https://www.kaggle.com/datasets/mujtabamatin/air-quality-and-pollution-assessment

Correlation Matrix