MaRz: Machine Learning on the Fly
MaRz: Machine Learning on the Fly
January 9, 2023
Abstract: This research concerns machine learning on the fly, for problems where learning data changes continually, or where waiting for the system to learn is impractical. The principle behind MaRz (Machine Learning in Real Time by Fuzzification) is a fuzzy interpretation of data. This is a quantitative expression of the fact that each datum need not be taken literally. For example, a particular student with SAT score 1300 and college GPA of 3.5, among hundreds of thousands, can be just as appropriately thought of as having approximately 1300 and 3.5 scores respectively. MaRz expresses this via fuzzy values centered on traditional “crisp” values. We show results on increasingly complex data sets and discuss the technical issues involved.
Speaker Bio: Eric Braude has a Ph.D. in mathematics from Columbia University and master’s degree in computer science. He taught at CUNY and Penn State, followed by 12 years in government and industry as a software engineer, scientist, and manager. He is an associate professor of computer science at Boston University’s Metropolitan College. Eric has written, cowritten, or edited six books. His research concerns machine learning and program design.