https://github.com/chamale-rac/cervical-cancer-diagnosis
Cervical Cancer Diagnosis (CC3084 DATA SCIENCE - LAB 1)
https://github.com/chamale-rac/cervical-cancer-diagnosis
Last synced: about 1 month ago
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Cervical Cancer Diagnosis (CC3084 DATA SCIENCE - LAB 1)
- Host: GitHub
- URL: https://github.com/chamale-rac/cervical-cancer-diagnosis
- Owner: chamale-rac
- License: gpl-3.0
- Created: 2024-07-16T22:40:15.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-07-22T04:10:40.000Z (9 months ago)
- Last Synced: 2025-01-26T04:42:13.313Z (3 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 8.07 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
Here is the updated README with more detailed content for the sections:
# Cervical Cancer Prediction
**CC3084 DATA SCIENCE - LAB 1**
> Samuel A. Chamalé, `[email protected]`
> Adrian Rodriguez, `[email protected]`
---
Overview •
Files •
Recommendations
## Overview
This project aims to predict the likelihood of cervical cancer based on various risk factors and medical history. Using a dataset containing attributes related to demographic information, behavioral habits, and medical history, we will perform data cleaning, exploratory data analysis (EDA), and verify the appliance of PCA and Apriori association rules.
## Files
- [`archive`](archive): Source data files and generated ones (original and cleaned datasets).
- [`eda&cleaning.ipynb`](eda&cleaning.ipynb): Initial exploratory data analysis notebook (Questions 1 to 7)
- [`pca.ipynb`](pca.ipynb): Principal components analysis (Question 8)
- [`apriori.ipynb`](apriori.ipynb): Association rules using Apriori algorithm (Question 9)
- [`findings&conclusions.ipynb`](findings&conclusions.ipynb): Final findings and conclusions about the entire process.
Feel free to reach out to us if you have any questions or need further assistance.
## Recommendations
While using Python, we highly recommend using a [virtual environment](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/) as good practice.