Machine Learning Workflow for Classification Analysis

This diagram illustrates the process of data preprocessing, model building, and performance evaluation for a machine learning classification task using the Wisconsin dataset. It covers data splitting, training, and the application of various models like SVM, KNN, Random Forest, AdaBoost, Naive Bayes, and XGBoost. The workflow also includes data scaling, performance evaluation, and output prediction.