study employed two algorithms: Bayesian inference and a weighted Support Vector Machine (SVM) algorithm based on the grey … the continuity and accuracy of predictions. The weighted SVM algorithm based on grey relational analysis improves the …

study employed two algorithms: Bayesian inference and a weighted Support Vector Machine (SVM) algorithm based on the grey … the continuity and accuracy of predictions. The weighted SVM algorithm based on grey relational analysis improves the …

Machine (SVM) technique is chosen for fake news classification, which is a highly robust and effective machine learning …, specifically, the SVM algorithm is chosen.nPreprocessing the text data reduced the dimensionality of the dataset by almost 50 %, as … is almost 75 % using SVM. Due to the fact that unstructured data and individual pre-processing steps can distort certain …

Vector Machine (SVM) is a powerful machine learning tool that has proven invaluable in classifying observations through … optimal hyperplane in higher dimensions. Despite their widespread use, SVM models encounter substantial challenges during the … computation time compared to conventional SVM approaches. …

Purpose This research explores support vector machine (SVM) with Gaussian radial basis function kernel (RBF) as the … conduct classification model training and prediction for the accuracy of invalidation re-examination decisions through SVM … classification was 95.96%, this research’s outcomes confirmed the purpose of applying SVM with RBF to predict the patentability …