Breast_Cancer_Classification

The aim of this project is to classify breast cancer as either malignant or benign using the dataset from sckit-learn. It is a web application built using streamlit and deployed with heroku(link: https://breast-cancer-detection-heroku.herokuapp.com/). The app analyzes the given data and provides prediction accuracy for the various classification algorithms used i.e Support Vector Machine, Logistic Regression, K-Nearest Neighbor, Random Forest, Decision Trees and Naïve Bayes. The application allows for interactivity with the parameters of these classification algorithms. In addition, I have plot Confusion Matrix, Precision-Recall Curve and ROC curve for each of the classifications. For data visualization I have used Pandas, Matplotlib, Seaborn, Plotly and Numpy.