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Overfitting

468 bytes added, 23:46, 24 May 2014
Remedies for overfitting
===Randomly vary training examples===
 
This approach considers slight, somewhat artificial, variations of the training examples and checks whether the strategies learned for solving those examples generalize to the variations. This approach is better suited in situations where the set of externally provided examples is limited, but it is possible to tweak an example to create a new example.
 
This is an adaptation to human learning of the methods used for artificial data synthesis in machine learning.
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