Lung Cancer Prediction 🫁

This is a simple machine learning project for lung cancer prediction using an openly available dataset of hospital patients.

The final trained model has been built using scikit-learn's LogisticRegression, but optimized for multiclass classification using a Newton-Conjugate Gradient solver.

Setup

Prerequisites

1. Git
2. Python (at least 3.9.0) must be installed on your system.

After Python has been set up, install the virtualenv package to create and manage a virtual environment for this project. This helps you maintain the project's dependencies in a hassle-free manner, without installing any unnecessary packages globally throughout your system.

pip install virtualenv

1. Clone the Project

Clone this project to create a local copy of it on your system:

git clone "https://github.com/ravi-aratchige/lung-cancer-prediction.git"

Then, move into the project folder:

cd lung-cancer-prediction

2. Create a Virtual Environment

Create a virtual environment inside the project folder to isolate its dependencies:

python -m venv env

# or

python3 -m venv env

Next, activate the virtual environment:

# on Windows:
.\env\Scripts\activate

# on MacOS or Linux
source env/bin/activate

You can deactivate this environment when you are done working with the project:

# on Windows, MacOS or Linux
deactivate

3. Install Dependencies

Set up your project with the necessary packages and libraries. After activating the virtual environment, enter the following command:

pip install -r requirements.txt

4. Start Jupyter Server

After you have completed the above steps, you can start the Jupyter server to view the notebook.

jupyter notebook

Jupyter will begin serving in localhost:8888.

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This project is licensed under the Apache License.