Breast Cancer Detection using Logistic Regression

This project aims to predict whether a breast cancer tumor is malignant or benign based on a dataset of cell features from breast tissue. The classification model uses a Logistic Regression algorithm to distinguish between malignant and benign tumors.

Features

• Dataset: The dataset includes various features related to the characteristics of cell nuclei obtained from fine needle aspirates (FNA) of breast tissue.

• Classification: Using the features, a Logistic Regression model classifies the tumors into two categories:

  • Malignant (cancerous)
  • Benign (non-cancerous)

• Data Preprocessing: The features are preprocessed using pandas and numpy for easy manipulation and model input.

• Model Evaluation: The model's performance is evaluated based on the accuracy score of the classification.

Libraries and Tools

This project uses the following Python libraries:

• numpy
• pandas
• scikit-learn
  • LogisticRegression
  • train_test_split
  • accuracy_score

Dataset

The dataset used in this project is the Breast Cancer Wisconsin (Diagnostic) dataset, which contains 30 features describing the characteristics of cell nuclei present in breast cancer images. The features include radius, texture, perimeter, area, smoothness, compactness, concavity, concave points, symmetry, and fractal dimension.

Key attributes:

• Malignant (0): Cancerous tumors
• Benign (1): Non-cancerous tumors

How to Run

1. Clone the repository:

   git clone https://github.com/trivediayush/Breast-Cancer-Detection.git
   cd Breast-Cancer-Detection

2. Install dependencies:

   pip install -r requirements.txt

3. Run the model:

   • The model is implemented in Breast_Cancer.ipynb. You can run it by executing the following command:

   • After running the script, the model will make predictions for given input data and print whether the breast cancer is Malignant or Benign.

4. Input:

   • Example input format for predicting cancer type:

   input_data = (13.54, 14.36, 87.46, 566.3, 0.09779, 0.08129, 0.06664, 0.04781, 0.1885, 0.05766, 0.2699, 0.7886, 2.058, 23.56, 0.008462, 0.0146, 0.02387, 0.01315, 0.0198, 0.0023, 15.11, 19.26, 99.7, 711.2, 0.144, 0.1773, 0.239, 0.1288, 0.2977, 0.07259)

5. Output:

   • The script will output whether the breast cancer is Malignant or Benign.