The Applied Research Of The Filter And Wrapper Feature Selection

Feature selection is the key problem of pattern recognition, Feature selectionaccording to the evaluation strategies that consider classifier performance will featureselection method based on filtering into feature selection algorithm based on embeddedand feature selection algorithm.First of all, first introduced the feature selection algorithm based on filtering. Basedon the characteristics of filter algorithm is a kind of computation efficiency of thealgorithm is high, mainly adopts and classification task all kinds of relevant standards, toselect the most appropriate related standards on the characteristics of the classification.This article USES the filtering feature selection algorithm are mainly Fisher lineardiscrimination criterion, the biggest related minimum redundancy standards, will the twotypes of standards applied to ECoG cortical brain electrical signal, the data of 64channels feature selection. And the two methods of the sort that channel characteristicsand the airspace subspace method of feature extraction make combined results show thebiggest related minimum redundancy standards on cortex of eeg channel selectionprocess meaningful research. Then analyzed based on heuristic search strategy filteralgorithm, and the characteristics of the filter algorithm applied to wine dataclassification, through the linear classifier after analysis, it is concluded that these featureselection algorithm for wine data classification effect was improved.Then, this paper introduces the feature selection algorithm based on embedded.Based on embedded feature selection algorithm is will the capability of classifier toconsider feature selection process, through the classifier performance to choosecorresponding characteristics. This paper used the support vector machine (SVM)regression characteristic elimination algorithm, and also applied to EcoG cortex eegsignals. Another method is based on the characteristics of the weight increase or decreaseof embedded feature selection algorithm, this kind of algorithm is applied to wine in theprocess of data classification and validate it to improve wine classification algorithm hasvery great help. Finally, the differential evolution algorithm and the airspace subspacedecomposition of combining a new embedded feature selection algorithm, and the basedon this kind of embedded feature selection algorithm was improved. Experimental resultsverify the method of cortex of eeg channel selection process of the effect very good,which shows that this method has a certain research significance.