I am using 5g dual connectivity network dataset which consists of training samples and labels and then SVM-SMO get trained on that dataset and trained SVM-SMO model can be applied on new request for ...

The rapid growth of data in the digital era has made classification techniques a critical component of machine learning, particularly in supervised learning methods. These techniques enable computers ...

Machine Learning in Manufacturing: ... the regularization parameter value and the gamma coefficient value of the SVM algorithm are optimized using Horse Optimization Algorithm (HOA), (3) the HOA based ...

3: SVM. Originated in 1963, Support Vector Machine (SVM) is a core algorithm that crops up frequently in new research. Under SVM, vectors map the relative disposition of data points in a dataset, ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...