matlab - What is the significance of data set sampling during Bagging method for dynamic classifier selection method?

Question

During Dynamic Classifier Selection, in training stage we apply bagging to the training set to get pool of classifiers. Bagging includes the process of dividing/sampling the training data set into number of data subsets containing elements with replacement and subsequently these each data subsets is trained by learners to get the values. The predicted values from each classifier is then compared by voting method and the classifier with highest accuracy value is selected. In the following condition during data subset creation why there is need of sampling of main training set(i.e dividing the data set into number of data subsets), why cant we give the whole training data as input to each learners going to be used for training the data set?

标签： matlabmachine-learningclassification