Showing posts with label generalization error. Show all posts
Showing posts with label generalization error. Show all posts

AI Terms Glossary - ADABOOST


ADABOOST is a way for enhancing machine learning methods that was recently created.

It has the potential to greatly enhance the performance of classification methods (e.g., decision trees).

It works by repeatedly applying the procedure to the data, analyzing the findings, and then reweighting the observations to provide more weight to the misclassified instances.

By a majority vote of the individual classifiers, the final classifier employs all of the intermediate classifiers to categorize an observation.

It also has the intriguing virtue of continuing to lower the generalization error (i.e., the error in a test set) long after the training set error has stopped dropping or hit 0.

See Also: 

arcing, Bootstrap AGGregation (bagging)

~ Jai Krishna Ponnappan

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Be sure to refer to the complete & active AI Terms Glossary here.

You may also want to read more about Artificial Intelligence here.

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