Inductive Learning for Case-Based Diagnosis with Multiple Faults
作者： Joachim Baumeister , Martin Atzmüller , Frank Puppe
关键词:
摘要: We present adapted inductive methods for learningsimilarities, parameter weights and diagnostic profiles case-based reasoning. All of these can be refined incrementally by applyingdif ferent types background knowledge. Diagnostic are used extending the conventional CBR to solve cases with multiple faults. The context our work is supplement a medical documentation consultation system techniques, we an evaluation real-world case base.
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