| 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 |