AhmedHosamMorgan/Supervised-Unsupervised-Machine-Learning-Models-on-Breast-Cancer-Dataset-Using-Ai.

End of semester project for AI at Future University in Egypt End of Semester Project For Machine Learning For Artificial intelligence Subject - Future University In Egypt (FUE) Supervised/Unsupervised Machine Learning Models on “Breast Cancer” Dataset Using Ai. # Breast Cancer Diagnosis Prediction This project aims to predict breast cancer diagnosis using machine learning techniques. It utilizes the Breast Cancer Wisconsin (Diagnostic) dataset, available in the `data.csv` file, containing various features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. The target variable, `'diagnosis'`, indicates whether the tumor is malignant (M) or benign (B). ## Workflow Overview 1. **Data Preprocessing:** - Load the dataset using Pandas. - Separate features (`X`) and the target variable (`y`). - Encode the target variable into binary labels (Malignant: 1, Benign: 0). - Scale the features using StandardScaler to ensure uniformity in data distribution. 2. **Model Training and Evaluation:** - Employ Linear Regression for predicting the diagnosis. - Utilize k-fold cross-validation (k=3) to evaluate model performance. - Calculate evaluation metrics such as Mean Squared Error (MSE), R-squared, and Mean Absolute Error (MAE) to assess the model's accuracy. 3. **K-means Clustering:** - Apply K-means clustering to identify patterns within the dataset. - Determine the optimal number of clusters using the Elbow Method. - Calculate the Sum of Squared Errors (SSE) and Silhouette Coefficient to evaluate clustering performance. 4. **Visualization:** - Plot the clusters obtained from K-means clustering, along with the centroids. ## Instructions To run the project: 1. Ensure you have Python installed on your system. 2. Clone this repository to your local machine: ```bash git clone github.com ``` 3. Install the required Python libraries using pip: ```bash pip install pandas scikit-learn matplotlib ``` 4. Run the `main.py` script: ```bash python main. …