Abstract
Concept formation is a machine-learning based approach to cluster analysis of symbolic data. So far, several techniques have been proposed. The system FAVORIT, developed in our laboratory, has the ability to reflect such dynamic aspects of learning as step-by-step forgetting and strengthening the pieces of knowledge. We explain the basic features of FAVORIT and briefly report on the experiments demonstrating the ability of our approach (1) to cope with noisy and incomplete data and (2) to simplify the internal representation of learned concepts.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 19-25 |
| Number of pages | 7 |
| Journal | Pattern Recognition Letters |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1992 |
| Externally published | Yes |
Keywords
- ageing of knowledge
- concept formation
- Machine learning
- prediction of unknown attribute values
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Electrical and Electronic Engineering
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Cite this
Krizakova, I., & Kubat, M. (1992). FAVORIT: Concept formation with ageing of knowledge. Pattern Recognition Letters, 13(1), 19-25. https://doi.org/10.1016/0167-8655(92)90110-L