Category learning (CL), a neural network classification model, is compared with a classical knowledge acquisition tool, Probabilistic Rule Generator (PRG), and the result is discussed.
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https://www.riss.kr/link?id=A19589373
1988
Korean
400
학술저널
27-36(10쪽)
0
상세조회0
다운로드다국어 초록 (Multilingual Abstract)
Category learning (CL), a neural network classification model, is compared with a classical knowledge acquisition tool, Probabilistic Rule Generator (PRG), and the result is discussed.
Category learning (CL), a neural network classification model, is compared with a classical knowledge acquisition tool, Probabilistic Rule Generator (PRG), and the result is discussed.
자동차 TIRE NOISE의 SIMULATION에 관한 연구
The Uniqueness of Orthorhombic System in X-Ray Diffraction Photographs