Method of reducing amount of data required to achieve neural net

Details Method of reducing amount of data required to achieve neural net Method of reducing amount of data required to achieve neural net

1994-06-21

1997-04-15

Hafiz, Tariq R.

395 20, 395 21, G06E 100, G06E 300, G06F 1517

Patent

active

056218613

ABSTRACT:
A method of reducing the amount of learning data required to execute a neural network learning procedure, whereby an original entire set of learning sample data are divided, using cluster analysis of the original entire learning sample data, into a plurality of sub-groups, with the sub-groups being respectively applied to a neural network as learning data and with respective values of recognition index obtained thereby for the neural network being judged, to select the smallest sub-group which will provide a value of recognition index that is at least equal to the recognition index obtainable by using the original entire learning data.

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