A critical review for developing affinity set method for multi classification and prediction
Machine learning, a branch of artificial Intelligence targets to make predictions more accurate. Machine Learning methods have been widely used. The notion of affinity set which is one of the machine learning methods can be defined as the distance or closeness between two objects. Unlike the fuzzy S...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/40280/ |
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| Summary: | Machine learning, a branch of artificial Intelligence targets to make predictions more accurate. Machine Learning methods have been widely used. The notion of affinity set which is one of the machine learning methods can be defined as the distance or closeness between two objects. Unlike the fuzzy Set and Rough Set, the affinity can deal with third objects and deals with time dimension. In addition, it could deal with entities or abstract side by side with real objects. Indeed, the existing models of affinity are developed for binary classification or prediction. This review highlighted that the existing models of affinity set should be developed in order to provide a multi classification or multi prediction. |
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