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Next: Measure Performance Previous: Danger: Overfit
Procedure
- Collect large set of examples (as large and diverse as possible)
- Divide into 2 disjoint sets (training set and test set)
- Learn concept based on training set, generating hypothesis H
- Classify test set examples using H, measure percentage
correctly classified
- Should demonstrate improved performance as training set size increases
(learning curve)
How quickly does it learn?
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