An examination of a classification model with partial least square based dimension reduction
Guozheng Li · Journal of Shandong University · 2010
Among various methods,partial least square based dimension reduction(PLSDR)is one of the most effective,and has been applied in many fields such as the analysis of microarray data.But the problem of choosing a classification model with PLSDR has often been neglected,and different classification models are arbitrarily applied.To this problem,an examination of different classification models with PLSDR by intensive experiments was given.Furthermore,by using the paired two-tailed t-test,an artificial neural network,logistic discrimination and linear support vector machine is suggested to be good performance classification models used with PLSDR.