A Hybrid Method for Fast Finding the Reduct with the Best Classification Accuracy

Advances in Electrical and Computer Engineering

关键词: artificial intelligence;    classification algorithms;    decision trees;    discernibility function;    feature selection;   

DOI  :  10.4316/AECE.2013.04010

来源: DOAJ

【 摘 要 】

Usually a dataset has a lot of reducts finding all of which is known to be an NP hard problem.On the other hand, different reducts of a dataset may provide different classification accuracies.Usually, for every dataset, there is only a reduct with the best classification accuracy to obtainthis best one, firstly we obtain the group of attributes that are dominant for the given dataset byusing the decision tree algorithm. Secondly we complete this group up to reducts by using discernibilityfunction techniques. Finally, we select only one reduct with the best classification accuracy by usingdata mining classification algorithms. The experimental results for datasets indicate that the classificationaccuracy is improved by removing the irrelevant features and using the simplified attribute set whichis derived from proposed method.

【 授权许可】

Unknown