support vector machine (SVM)
A Support Vector Machine (SVM) is a learning system, comparable to Deep Learning, with which objects can be automatically classified and assigned to corresponding classes. The class boundaries formed in the process have the greatest possible distance to other objects.
Support Vector Machine is a method of classifying objects in which the objects are assigned to one of two classes. The class division can be done by a linear or non-linear dividing line. The objects are sorted by similar patterns, colors or other features and assigned to a class.
The SVM technique also supports automatic text classification. For this, it uses a word- document matrix corresponding to a document collection of keywords. This complex matrix, which can consist of several thousand columns and rows, is transposed in SVM techniques into a space that has as many dimensions as the matrix keywords. In this mathematical model, where each keyword forms an axis, linear and polygonal planes are determined as classifiers over which the classification of new documents is performed.