Drawbacks of Find-S algorithm

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1.Find-S is sensitive to noise that is present in training examples.

2. There is no guarantee that the h returned by Find-S is the only h that fits the data

3.Several maximally specific hypothesis may exist that fits the data, but Find-S will output only one.

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Difference between Find-S and Candidate-Elimination Algorithms

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Find-S :

Find-S is guaranteed to output the most specific hypothesis h that best fits positive training examples.

The hypothesis h returned by Find-S will also fit negative examples as long as training examples are correct.

Candidate-Elimination:

Outputs a description of set of all hypotheses consistent with the training examples.

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