SVM
SVM uses python along with scikit-learn to identify 10 features and accurately predict the labels between 7 different types of glass in the UCI glass data set through the use of Support Vector Machines. This program uses five crossfold validation and spilts the data intro three sets to maximize the hyperparameters for the test dataset and compares the performance on the different types of Support Vector Machines