Separating core and noncore knowledge: An application of neural network rule extraction to a cross-national study of brand image perception
Recent advances in algorithms that extract rules from artificial neural networks make it feasible to use neural networks as a tool for acquiring knowledge hidden in the data. Findings are reported from the use of such algorithms to separate core and noncore knowledge in a cross-national study of aut...
محفوظ في:
المؤلفون الرئيسيون: | Setiono, Rudy, Pan, Shan L., Hsieh, Ming Huei, Azcarraga, Arnulfo P. |
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التنسيق: | text |
منشور في: |
Animo Repository
2005
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الموضوعات: | |
الوصول للمادة أونلاين: | https://animorepository.dlsu.edu.ph/faculty_research/2374 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3373/type/native/viewcontent |
الوسوم: |
إضافة وسم
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المؤسسة: | De La Salle University |
مواد مشابهة
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Separating core and noncore knowledge: An application of neural network rule extraction to a cross-national study of brand image perception
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