The project is about analyzing disaster data for a few countries in Africa and South America. The data files for 13 countries are collected from ‘
desinventar.xn--net-to0a. The project goes through 5 stages: Data Cleaning and Feature Engineering, Data Visualization, Principles Component Analysis, Regression and Classification.
# Disaster Classification Analysis
This repository contains datasets and analysis scripts for exploring disasters across Africa and South America. It covers data cleaning, visualization, feature engineering, dimensionality reduction (PCA), and classification.
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## Folder Structure
### Data Folders
- **`original_data/`**
Contains the originally downloaded datasets, divided into:
- `Africa/`
- `South_America/`
- **`cleaned_data/`**
Contains datasets after **Data Cleaning** and **Feature Engineering**.
- **`pca_data/`**
Contains datasets including PCA results and the datasets used for classification.
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## Script Descriptions
### 1. `Africa_combined.Rmd`
This script includes:
- **Data Cleaning**
- **Data Visualization**
- **PCA Analysis**
- **Regression Analysis**:
- Using the **originally cleaned dataset**.
- Using the **PCA-transformed dataset**.
Applied to **African countries**.
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### 2. `South_America_combined.Rmd`
This script includes:
- **Data Cleaning**
- **Data Visualization**
- **PCA Analysis**
- **Regression Analysis**:
- Using the **originally cleaned dataset**.
- Using the **PCA-transformed dataset**.
Applied to **South American countries**.
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### 3. `Classification_binary.Rmd`
This script performs **binary classification** to predict the **CONTINENT** where a disaster occurred (Africa or South America).
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### 4. `Classification_multi.Rmd`
This script performs **multi-class classification** to predict the **DISASTER CATEGORY**, which includes 17 different types of disasters.
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## How to Run
### Prerequisites
1. Install **R** (version 2024.04.2+764 or later).
2. Install **RStudio** (recommended for running `.Rmd` files).