Inexact MDL for linear manifold clusters
Robert M. Haralick, Art Diky, Xing Su, Nancy Yao-lan Kiang · 2016
We present a regularization technique based on the minimum description length (MDL) principle for the linear manifold clustering. We suggest an inexact minimum description length method based on describing the data structure as linear manifold clusters. We examine the behavior of the proposed method and compare it performance against simulated clustering results of various dimensionality and structure. Finally, we empirically evaluate the proposed technique on a climate data.