The novel Reference frame best fit fiber bundle shape recognition by Machine Learning

Abstract

This is about frames of reference and their relation to classification. A classification is needed to establish a frame of reference and, with a frame of reference, measurements and further classifications are possible. The topic is discussed in terms of a method that chooses the”best” among alternative frames of reference. We will describe how measurements induce a fiber bundle that projects from a total space of objects onto a base space of measurement values. Local inverses of this projection, or ”sections” of the fiber bundle play the role of frames of reference or ideal objects that are attached to the data, as the nearest neighbor in the fiber. In this formalism the invariant properties of personality are parameterized by the variant ones, which are measured, and classification is seen as inverse to measurement. Rather than proving theorems, the article has two goals: to provide engineers with a recipe for solving classification problems; and to bring the concept of moving frames from differential geometry into a broader discussion of classification.