1
Self-organization schemes in regression analysis | |
Author | Khine Shwe Phyu |
Call Number | AIT Thesis no.CS-93-29 |
Subject(s) | Regression analysis |
Note | A thesis submitted in partial fulfillment of the requirement for the degree of Master of Science |
Publisher | Asian Institute of Technology |
Abstract | Self-organizing map is an attractive neural net that can be applied to the problem of dynamic knot allocation for nonparametric regression analysis. The classical approach to the optimal knot location is a computationally hard problem of combinatorial complexity even for single variable function. The problem of piecewise linear regression for a function of single independent variable can be stated as the problem of forming two dimensional topological maps for a set of samples in two dimensional input space. The output units have correct topological order in the mapping of giving the two- dimensional input space. This proposed algorithm produced optimal placement of knots and the response values of immediate data points in very reasonable processing time. |
Year | 1993 |
Type | Thesis |
School | School of Engineering and Technology (SET) |
Department | Department of Information and Communications Technologies (DICT) |
Academic Program/FoS | Computer Science (CS) |
Chairperson(s) | Sadananda, Ramakoti; |
Examination Committee(s) | Huynh, Ngoc Phien;Yulu, Qi; |
Degree | Thesis (M.Sc.) - Asian Institute of Technology, 1993 |