Adaptive Learning Methods for Nonlinear System Modeling

Chapter 9

Online Nonlinear Modeling via Self-Organizing Trees

Nuri Denizcan Vanli^⁎; Suleyman Serdar Kozat^{†    ⁎}Massachusetts Institute of Technology, Laboratory for Information and Decision Systems, Cambridge, MA, United States^†Bilkent University, Ankara, Turkey

Abstract

We study online supervised learning and introduce regression and classification algorithms based on self-organizing trees (SOTs), which adaptively partition the feature space into small regions and combine simple local learners defined in these regions. The proposed algorithms sequentially minimize the cumulative loss by learning both the partitioning of the feature space and the parameters of the local learners defined in each region. The output of the algorithm at each ...