The data set is collected from Addis Ababa Sub-city police departments for master's research work. The data set has been prepared from manual records of road traffic accidents of the year 2017-20. All the sensitive information has been excluded during data encoding and finally it has 32 features and 12316 instances of the accident. Then it is preprocessed and for identification of major causes of the accident by analyzing it using different machine learning classification algorithms.
Source of Dataset: Click here
The target feature is Accident_severity which is a multi-class variable. The task is to classify this variable based on the other 31 features step-by-step by going through each day's task. The metric used for evaluation is f1-score
This project requires Python and the following Python Libraries installed:
Following two packages are optional
- Streamlit (Only required to run the web application)
You will also need to have software installed to run and execute a Jupyter Notebook or you can use Google Collab
If you do not have Python installed yet, it is highly recommended that you install the Anaconda distribution of Python, which already has the above packages and more included.
Python Notebooks are provided in the Notebook folder. The required datasets are included in the Dataset Folder.
In a terminal or command window, navigate to the top-level project directory RTA-PROJECT/ (that contains this README) and then navigate to Notebook and run one of the following commands:
ipython notebook "Notebook_name"or
jupyter notebook "Notebook_name"or open with Juoyter Lab
jupyter labThis will open the Jupyter Notebook software and project file in your browser.
In a terminal or command window, navigate to the top-level project directory RTA-PROJECT/ (that contains this README) and run the following command:
streamlit run app.py