Learning From Data ( Case-Based Reasoning )


Lecturer : Leon Abdillah



Case-Based Reasoning

It is reasoning from relevant past cases in a way similar to human’s use of past experiences to arrive at conclusions.

• Case-based reasoning is a technique that records and documents cases and then searches the appropriate cases to determine their usefulness in solving new cases presented to the expert.

• The aim is to bring up the most similar historical case that matches the present case.

• Adding new cases and reclassifying the case library usually expands knowledge.

• A case library may require considerable database storage as well as an efficient re- trieval system.

Case-based reasoning (CBR), broadly construed, is the process of solving new problems based on the solutions of similar past problems. An auto mechanic who fixes an engine by recalling another car that exhibited similar symptoms is using case-based reasoning. A lawyer who advocates a particular outcome in a trial based on legal precedents or a judge who creates case law is using case-based reasoning. So, too, an engineer copying working elements of nature (practicing biomimicry), is treating nature as a database of solutions to problems. Case-based reasoning is a prominent kind of analogy making.

It has been argued that case-based reasoning is not only a powerful method for computer reasoning, but also a pervasive behavior in everyday human problem solving; or, more radically, that all reasoning is based on past cases personally experienced. This view is related to prototype theory, which is most deeply explored in cognitive science.



Case-Based Reasoning " Library "


Group Member : 
 1. Randhy Pratama - 10141217
 2. Rano Karno - 10141020
 3. M. Muslim - 11141275
 4. Endang Kurnia - 10141025
 5. M. Roland Zen - 10141129
 6. Elsa Oktarina - 10141019
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