HIGH-DIMENSIONAL PRECANCEROUS LESIONS OF COLORECTAL CANCER DATA CLASSIFICATION BASED ON MMTS-ADABOOST
In order to reduce the incidence and mortality of colorectal cancer by improving the classification accuracy of precancerous lesions,a high-dimensional data classification algorithm based on MMTS-AdaBoost is proposed to optimize the classification algorithm of high-dimensional data and improve the classification performance.The dimension reduction was achieved by applying the proper orthogonal decomposition idea to Mahalanobis-Taguchi system and improving the Mahalanobis-Taguchi system to acquire important feature variables.Using the feature variables obtained by dimension reduction,the AdaBoost algorithm was used to classify the types of precancerous lesions.The experimental results show that compared with the mrmr-AdaBoost and chisquare-AdaBoost algorithms that use dimension reduction,as well as the classic classification algorithms such as AdaBoost,BP network,NB,and SVM,the F1 and G-mean of the MMTS-AdaBoost are higher,and the classification performance is better.
Precancerous lesions of colorectal cancerHigh-dimensional data classificationMahalanobis-Taguchi systemAdaBoostProper orthogonal decomposition
国家科技期刊平台
NSTL
万方数据
维普
