| Author | Manandhar, Suman K. |
| Call Number | AIT Thesis no.CS-95-15 |
| Subject(s) | Neural networks (Computer science)
|
| Note | A thesis submitted in partial fulfillment of the requirement for the degree of Master of
Engineering |
| Publisher | Asian Institute of Technology |
| Abstract | Neural networks have been described as opaque systems by their critics because the knowledge learned by the network is implicitly coded in the weight matrices. These weight matrices, however, can be analyzed using computer programs and rules can be extracted that explicitly state what the network has learned. A rule extraction algorithm called NeuRuleMaker has been described and implemented. Three case studies have been taken as real-world examples and the extracted rulebase in each case is shown to perform close to the neural network itself from which the rules were extracted. It is argued that rule extraction can be a valuable tool for expert system developers and may help popularize "consumer grade" expert systems. |
| Year | 1995 |
| 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) | Stueart, Robert D.;Yulu, Qi; |
| Scholarship Donor(s) | The Government of Austria; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 1995 |