This project aims to predict the presence of breast cancer using a logistic regression model. It classifies two types of tumors Benign and Malignant. The logistic regression model is a popular machine learning algorithm for binary classification tasks.
The dataset used for this project is the Breast Cancer Wisconsin (Diagnostic) Dataset, available on kaggle.It contains features computed from digitized images of fine needle aspirates (FNA) of breast mass. The features include various characteristics of the cell nuclei, such as radius, texture, perimeter, area, smoothness, compactness, concavity, symmetry, and fractal dimension.
Make sure you have the following dependencies installed:
1.Python (version 3.0 or higher) 2.NumPy 3.Pandas 4.Scikit-learn
You can install the required packages by running the following command: python breast_cancer_prediction.py
After running the script, you will see the accuracy of the logistic regression model on the testing set.