Which data mining technique derives rules from real-world case examples?

Case-Based Reasoning (CBR) is a data mining and artificial intelligence technique that solves new problems by using solutions from previous real-world cases. Instead of creating a solution from scratch, it searches for similar past cases and applies the knowledge gained from those examples to the current problem.

The basic idea behind Case-Based Reasoning is that similar problems often have similar solutions. When a new case is presented, the system compares it with previously stored cases in its knowledge base. If it finds a close match, it adapts the earlier solution to fit the new situation. This approach is widely used in fields such as medical diagnosis, customer support, legal decision-making, and technical troubleshooting, where past experience plays an important role in solving problems.

Key Point:

• Case-Based Reasoning (CBR): Solves new problems using solutions from similar past cases. 


• Rule Discovery: Finds hidden rules and relationships in data.


• Neural Networks: Learn patterns from training data for prediction and classification.


• Signal Processing: Processes and analyzes digital or analog signals.

Exam Tip:

                 Remember that Case-Based Reasoning (CBR) is based on the principle of "learning from previous experience."