| Author | Thanakorn Sakchaicharoenkul |
| Call Number | AIT Thesis no. CS-99-16 |
| Subject(s) | Genetic algorithms
|
| Note | A thesis submitted in the partial fulfillment of the requirements for the degree of Master
of Engineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Abstract | Feature selection is the method that used to reduce the redundant features. In this
study, the methodology consists of several stages that are related to one another. Genetic
Algorithm is applied as a feature selection procedure. Many of statistic knowledge are
used to create new fitness functions and new classification procedures. The new fitness
functions are based on coefficient of determination and partial correlation coefficient.
The new classification procedures are based on Linear Regression Analysis and Linear
Discriminant Analysis.
The aim of this work is to make proposed feature selection procedure generate the
better results, both remaining features and predicted accuracy, than the prior methods.
And the learning period can be shortened. Finally, GA with Linear Discriminant and two
proposed fitness functions can generate the better results. |
| Year | 1999 |
| 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) | Yulu, Qi |
| Examination Committee(s) | Sadananda, Ramakoti;Phan Minh Dung |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 1999 |