Overview of Support Vector Machines (SVM) SVM is a supervised machine learning algorithm used for classification and regression tasks. It works by finding a hyperplane that best separates different ...

Objective: To implement Support Vector Machines for both linear and non-linear (RBF kernel) classification, visualize decision boundaries, and evaluate model performance using cross-validation and ...

Finally, after implementing SVM for multiclass classification problems, you need to evaluate the performance of the model using some metrics, such as accuracy, precision, recall, or F1-score.

In this reasearch, we propose a reliable skin disease detection system by integrating a deep learning model, ResNet50, with a Support Vector Machine (SVM) classifier. Using the recommended methodology ...