Hello guys! I am working with some classifiers ( SVM,C4.5,RNA,etc) using 10-C.V. Once I have the model of each one, I make the validation of these models in one dataset. Then,with my model and the dataset, I extract a confusion matrix to know the capacity of prediction from the model. And finally, I extract the accuracy of this prediction based on the diagonal from the confusion matrix. The fact is that I need to do that process for each partition of 10-CV. I need to do 10 times the previous process to obtain the accuracy of each partition from CV to know how response each partition in the prediction of the dataset. Do you know any method in R to do it? Thanks a lot, of course! [[alternative HTML version deleted]]
Anyone? Thanks! 2013/4/4 Nicolás Sánchez <enikok@gmail.com>> Hello guys! > > I am working with some classifiers ( SVM,C4.5,RNA,etc) using 10-C.V. > > Once I have the model of each one, I make the validation of these models > in one dataset. Then,with my model and the dataset, I extract a confusion > matrix to know the capacity of prediction from the model. And finally, I > extract the accuracy of this prediction based on the diagonal from the > confusion matrix. > > The fact is that I need to do that process for each partition of 10-CV. I > need to do 10 times the previous process to obtain the accuracy of each > partition from CV to know how response each partition in the prediction of > the dataset. > > Do you know any method in R to do it? > > Thanks a lot, of course! >[[alternative HTML version deleted]]