Design problem solving: a task analysis
AI Magazine
Characterizing the applicability of classification algorithms using meta-level learning
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
CommonKADS: A Comprehensive Methodology for KBS Development
IEEE Expert: Intelligent Systems and Their Applications
A large deviation approach to normality testing
Computational Statistics & Data Analysis
An MDA approach to knowledge engineering
Expert Systems with Applications: An International Journal
Association rule-based feature selection method for Alzheimer's disease diagnosis
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
The aim of this paper is to present a knowledge-based approach to supervised classifier design. For this purpose, an expert system has been built following the Common KADS methodology. Classifier design is seen as a general design problem and a modified version of the well-known Propose-Critique-Modify method is proposed as a suitable strategy to solve it. In this context, a number of heuristics are used to shrink the search in the space of possible designs. Although the system is evaluated on different datasets, special emphasis is put on a particular problem: Alzheimer's diagnosis.