Tumor Classification — Machine Learning

Project Overview

• Purpose: Classify tumors using the provided dataset and a Jupyter notebook.
• Notebook: notebook/Tumor-Classification-ML.ipynb
• Data: data/UTF-8cancer_tumor_dataset2.csv
• Models: Logistic Regression, Random Forest, SVM
• Evaluation Metrics: Accuracy/Precision/Recall/F1-score

Setup

1. Create a virtual environment:

   python -m venv .venv
   .\.venv\Scripts\Activate.ps1

2. Install dependencies:

   pip install -r requirements.txt

Usage

• Open and run the notebook notebook/Tumor-Classification-ML.ipynb in Jupyter.
• Ensure data/UTF-8cancer_tumor_dataset2.csv is present.

How to create a README locally

You can create or update this file in PowerShell:

type nul > README.md
notepad README.md

Or write content directly:

@"
# My Title
Short description...
"@ > README.md

Contact

• Maintainer: Jonathan Mishayel — Data Science UG
• Email: jonathanmishayel00@gmail.com
• GitHub: https://github.com/JonathanMishayel
• Preferred support: Please open an issue on this repository for bugs or questions.