this project uses generated data to be able to predict malaria outbreaks in Cameroon
## Malaria Outbreak Prediction Model
A machine learning system that predicts malaria outbreaks using environmental, healthcare, and socioeconomic factors through Random Forest classification.
## Project Structure
```MALARIA/
├── venv/
├── .coverage
├── cleaning.py
├── confusion_matrix.png
├── coverage.xml
├── dim_dates.csv
├── dim_demographics.csv
├── dim_environment.csv
├── dim_health_initiatives.csv
├── dim_healthcare.csv
├── dim_infrastructure.csv
├── dim_location.csv
├── dim_prevention.csv
├── dim_socioeconomic.csv
├── dim_weather.csv
├── fact_malaria_cases.csv
├── feature_importance.csv
├── feature_importance.png
├── loading.py
├── model.py
├── processed_data.csv
└── test_malaria_db.py
```
## Overview
```This project implements a predictive model for malaria outbreak detection using machine learning techniques. The system analyzes multiple dimensions of data including:
Environmental factors
Demographic information
Healthcare accessibility
Infrastructure data
Prevention measures
Socioeconomic indicators
Weather patterns
```
## Data Sources
```The project uses a dimensional data model with the following key files:
Fact Table: fact_malaria_cases.csv - Contains the main malaria case records
Dimension Tables:
dim_dates.csv - Temporal dimensions
dim_demographics.csv - Population demographics
dim_environment.csv - Environmental factors
dim_health_initiatives.csv - Health programs and initiatives
dim_healthcare.csv - Healthcare facility information
dim_infrastructure.csv - Infrastructure availability
dim_location.csv - Geographical information
dim_prevention.csv - Malaria prevention measures
dim_socioeconomic.csv - Socioeconomic indicators
dim_weather.csv - Weather-related data
```
## Key Components
```Data Processing
cleaning.py: Handles data cleaning and preprocessing
loading.py: Manages data loading and ETL processes
Model
model.py: Contains the Random Forest implementation
test_malaria_db.py: Test suite for database operations
```
## Installation
```import the sql …