Graphs for Pattern Recognition

Pattern recognition, infeasible systems of linear inequalities, and graphs

Full-function complexes of pattern recognition allow a human or technological user to mine relevant feature data in two main directions that can be considered interconnected, depending on the goals that must be achieved by the complexes.

One direction of data mining in pattern recognition is most often referred to as unsupervised learning. The complex deals with a massive collection of vectors whose components represent qualitative or quantitative descriptions of various parameters that are specific for the problem domain of the user. Although some categorical labels could have preliminarily been assigned to those vectors, in order to reflect a knowledge of the domain, ...